1. Introduction to Artificial Intelligence and Machine Learning: Applications and Tools 2. Artificial Intelligen

May 27, 2024

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Artificial Intelligence, Machine Learning, Data Science, Applications, Tools

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1. Introduction to Artificial Intelligence and Machine Learning: Applications and Tools 2. Artificial Intelligen

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Yapay Zeka- Genel Bakış Giriş-Genel Bakış
Yapay Zeka Nedir? Yapay Zeka veriyi anlamlandırma sanatı diyebilir miyiz?
Farklar Nedir? Raporlama Analitik Yapay Zeka
Analitik Tipleri
Sektör Bazlı Kullanım Örnekleri Oluşturalım Telekomünikasyon Finans Eğitim Gıda Tarım ve Hayvancılık Sağlık Ulaşım Perakendecilik E-ticaret Savunma Madencilik Üretim İmalat Eğlence Turizm Enerji
Yapay Zeka Kullanım Senaryoları Metinden Sese, Sesten Metine Dönüşüm Ses Tanıma ve Ses Klonlama Tahmine Dayalı Analitik Nesne Tespiti Tahmine Dayalı Arıza Giderme Nesne Tanıma Müşteri Öngörüsü Sohbet Robotları Robotik Metinden Video Üretimi Yapay Zeka Otomasyon Akıl Yürütme Karar Verme Problem Çözme Metinden Ses Üretimi Dolandırıcılık Tespiti Büyük Dil Modelleri Oyun Zekası Sentetik Veri Üretimi Sesli Asistan Anlam Çıkarma Market Analizleri Duygu Analizleri
Yapay Zeka vs Makine Öğrenmesi vs Derin Öğrenme vs Üretken Yapay Zeka
YZ-MÖ-DÖ (AI-ML-DL) Yapay Zeka Derin öğrenme Makine Öğrenmesi Supervised Unsupervised Yapısal olmayan veri! Reinforcement
Structured vs Unstructed Veri
Makine Öğrenmesi Tipleri
Makine Öğrenmesi Tipleri- Örnek Tablo
Makine Öğrenmesi Tipleri- Algoritmalar
Sınıflandırma-Kümeleme
Yapay Zeka İçin Nerden Başlanabilir? Bilgisayar Bilimleri Matematik & İstatistik Programlama Dili • Python Kitap Önerisi • AI Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, Peter Bruce https://a.co/d/e1R4nK9 Naked Statistics, Charles Wheelan Yapay Zeka Önemli Bazı Kütüphaneler • Tensorflow • Keras • PyTorch • NumPy • SciPy • Scikit-Learn • OpenCV vb. Mathematician & Statistician Engineer Computer Scientist (e.g. Data Engineer) • Data Scientist Büyük Veri Bilgisi ve Araçları • SQL, PL SQL • MSSQL, MySQL, PostgreSQL • Hadoop • Hive • Pig • Hbase • Cassandra • Spark • Elasticsearch • Kafka, RabbitMQ • Cloud Computing (AWS, Microsof, Google Cloud, IBM vb.) ve niceleri.. İş Alanı Bilgisi Software Developer Data Analyst • • • • • • • • • • • • • • Telekomünikasyon, Finans, Eğitim, Gıda, Tarım ve Hayvancılık, Sağlık, Ulaşım, Perakendecilik, E-ticaret, Savunma, Madencilik, Sanayi, İmalat ve Üretim, Eğlence Manager & Marketing Specialist & Operation Specialist etc. Veri Görselleştirme&Raporlama&Analiz Etme • Python (Plotly, Matplotlib, Seaborn, Geoplotlib vs. data görselleştirme kütüphaneleri ile birlikte.) • SQL, • Tableau, • QlikView, • SAP BO, • Power BI TürkTelekom | Dahili | Kişisel Veri İçermez gibi sektörlerin herhangi bir alanında uzmanlaşmak, problemlere ve çözüm önerilerine sahip olacak kadar derin bilgi ve deneyim sahibi olmak ya da sahip olanlarla yakın iş yapmak. https://roadmap.sh/ai-data-scientist
https://www.sudeep.co/data-science/2018/02/09/Understanding-the-Data-Science-Lifecycle.htmlhttps://www.sudeep.co/data-science/2018/02/09/Understanding-the-Data-Science-Lifecycle.html

Newbie Video Cash Machine Review & Newbie Video Cash Machine $16,700 bonuses

Newbie Video Cash Machine Review & GIANT Bonus . Review in Detail of Newbie Video Cash Machine and Premium BONUSES of Newbie Video Cash Machine: http://crownreviews.com/newbie-video-cas…review-and-bonus/ Newbie Video Cash Machine is a real method that shows how to make 30 passive income streams with free traffic, no experience, no sales page, no product, no list… Inside this course, he even shows you an actual money magnet he has created along with proof that it’s earning him money… Newbie Video Cash Machine Newbie Video Cash Machine review Newbie Video Cash Machine review and bonus Newbie Video Cash Machine reviews Newbie Video Cash Machine reviews and bonuses Newbie Video Cash Machine discount Newbie Video Cash Machine bonus Newbie Video Cash Machine bonuses Newbie Video Cash Machine review and discount Newbie Video Cash Machine review in detail Newbie Video Cash Machine ultimate review Newbie Video Cash Machine coupon Newbie Video Cash Machine demo Newbie Video Cash Machine demo review Newbie Video Cash Machine huge discount Newbie Video Cash Machine discount coupon

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Email Tools review- Email Tools $27,300 bonus & discount

Email Tools Review demo - $22,700 bonus. Review in Detail of Email Tools and Premium BONUSES of Email Tools: http://crownreviews.com/email-tools-review-bonus Email Tools is a 4-in-1 suite that gives you the power to craft the perfect Email by addressing the 4 most crucial aspects of Email Marketing: Engagement, Personalization, Urgency, and Feedback. http://crownreviews.com/email-tools-review-bonus Email Tools Email Tools review Email Tools review and bonus Email Tools reviews Email Tools reviews and bonuses Email Tools discount Email Tools bonus Email Tools bonuses Email Tools review and discount Email Tools review in detail Email Tools ultimate review Email Tools coupon Email Tools demo Email Tools demo review Email Tools huge discount Email Tools discount coupon

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35 MM & 50 MM F MOUNT MACHINE VISION LENSES – MACHINE VISION INDIA

Machine Vision India is the first company in India manufacturing large format F-Mount Machine Vision lens. The company designs, develops & manufacture large format F-Mount. We holds very strong expertise in offering our customer's dedicated one-stop solution for all their optics requirements in building their machine vision imaging systems. "Recognized as best Machine Vision lens Supplier in the Industry" With strong in-house R&D & design efforts, our 35 MM & 50 MM F Mount lens are developed with optimal precision techniques & produce high quality images. Our camera lens are actively implemented in applications like in Machine Vision, color sorter, ITS/Surveillance, Medical Imaging Applications & many others etc. "Machine Vision India owned & maintained by BalaJi MicroTechnologies (BMT), India. For More information Please Visit Product page :- http://machine-vision-india.in/balaji-optics-f-mount-lenses.html http://machine-vision-india.in/balaji-optics-machine-vision-lenses.html Sales Contact: Office Tel:- 91-129-4006203, 91-129-6561300 Office Mobile:- 919643047670 Skype ID(For Product Inquiry): bmt.overseas Whatsapp(For Product Inquiry): 919643047670 Email (product inquiry):- sales.overseas@balaji-microtechnologies.com sales.india@balaji-microtechnologies.com machine vision, f mount lenses, f mount lens machine vision, f mount wide angle lens, f mount camera lens, f mount lens, machine vision lens, machine vision lenses F Mount Lenses, F mount lens, Machine Vision lens, machine vision, 50 mm F Mount Lens, 35mm F Mount Lenses, Machine Vision Lenses, colour sorter, Color sorter, Line scan camera, Line Scan Cameras.

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Artificial Intelligence

artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. In our smart and connected AI world, machines are increasing learning to sense, learn, reason, act and adapt to the real world. This is Artificial Intelligence.Â AI (artificial intelligence) for Doctor AI (artificial intelligence) for Farmers, AI (artificial intelligence) for autonomous car, AI (artificial intelligence) for banks, AI (artificial intelligence) for deep learning, AI (artificial intelligence) for Fun and games

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Artificial Intelligence

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Machine Learning Interview Questions and Answers | Machine Learning Interview Preparation | Edureka

** Machine Learning Training with Python: https://www.edureka.co/python ** This Machine Learning Interview Questions and Answers PPT will help you to prepare yourself for Data Science / Machine Learning interviews. This PPT is ideal for both beginners as well as professionals who want to learn or brush up their concepts in Machine Learning core-concepts, Machine Learning using Python and Machine Learning Scenarios. Below are the topics covered in this tutorial: 1. Machine Learning Core Interview Question 2. Machine Learning using Python Interview Question 3. Machine Learning Scenario based Interview Question Check out our playlist for more videos: http://bit.ly/2taym8X Follow us to never miss an update in the future. Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka

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Sales Intelligence Solution Study

Our Sales Intelligence covers one of the six categories presented in our Sales Enablement Best Practices Report. Sales Intelligence, also referred to as CRM Intelligence, is information used to accelerate the sales process and to improve the performance and productivity of the sales team. What separates Sales “Intelligence” from sales “data” is the level of insight and analysis, both real-time and socially influenced, integrated into the solution. At Demand Metric, we define a Sales Intelligence Solution as comprising the strategies, processes, technologies and tools that support the collection, integration, analysis, delivery and presentation of insights and information that increase sales. This study covers the following sections: - Executive Summary - What is Sales Intelligence? - Benefits of Sales Intelligence - The Sales Intelligence Solutions Landscape - Sales Intelligence Deployment Lifecycle - Vendor Selection Criteria - Action Plan - Analyst Bottom Line - About the Research Analysts - Our Solution Study Methodology - About Demand Metric There are 8 premium tools & templates linked inside of this solution study: - Sales Intelligence Maturity Assessment - Sales Enablement Framework - Sales Intelligence Strategy Scorecard - Sales Intelligence Vendors Matrix - Sales Intelligence System RFP Template - Sales Intelligence Vendor Evaluation Matrix - MarCom Plan Methodology - Sales Intelligence Metrics Dashboard To obtain this document, visit us at http://www.demandmetric.com/register

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How can e-learning reform the traditional education system?

What is traditional learning? Traditional learning relates to any type of training in a regular school setting using classic paper and pencil techniques. In brief, traditional relates to any type of teaching involving techniques typically used in any college. This may include typical instruction-style lecture, tasks and tests, and student homework, classical teaching pedagogy and teacher training, use of assigned textbooks and other course content, and an in-person instruction scheme. Traditional learning continues to be known to most learners today. While most of the components outlined above will be present, topics, textbooks, and some learning styles may differ. What is e-learning? Broadly speaking, e-learning relates to any kind of training that is electronically transmitted, generally over the internet. Think of any kind of educational material you might have consumed on platforms such as YouTube or other streaming sites or internet classes through universities or even virtual classrooms where students and teachers sign up remotely u2013all of these would count as examples of e-learning. E-learning is an inevitable evolution of the educational ecosystem with the growing ubiquity and fast spread of technology. It can be something as tiny as using electronic materials or something as enormous as massive open online courses that enable anyone to sign up to learn something new, anywhere and at any moment. Due to the many advantages it transfers to all stakeholders in the academic ecosystem, e-learning is increasingly becoming a feature in classrooms across school and institutes in the world. Importance of e-learning Overall, traditional learning is expensive, takes a long time and the results can vary. The importance of e-learning is now a given fact and it can offer an alternative that is much faster, cheaper and potentially better. In the fast-paced world of e-learning, the available technologies to make a course new and exciting are always changing, and course content can and should be updated quickly to give students the very latest information. This is especially important if the e-learning training is being given to employees in a sector where keeping up-to-date on industry developments is of the utmost importance. This is one of the reasons why many schools are now offering training via e-learning other reasons include low costs and the ability for students to study in their own time and place. What are the benefits of e-learning over the traditional education system? The advantages of including e-learning education system methodologies within the traditional education system or even implementing e-learning options at your school and college are many. Some key benefits of an e-learning education system are discussed in further detail below: One Time Setup Cost Many schools and institutes are hesitating to invest in the e-learning education system as they think that it would be too big to bear the price of such an effort. This is mainly due to infrastructure change. While schools and institutes are used to invest in products such as pens and paper, desks and benches, blackboards and classrooms, it makes sense that the cost of setting up an completely fresh teaching scheme must be closely adjusted against the budget of the school or institute. However, with most techniques or instruments in the e-learning education scheme, the price is mainly in the configuration, which is then mitigated over time because of how much it is used. This implies that the price is a one-time price u2013 an investment in the future where there are plenty of yields on such an investment. Increases Inclusivity for Stakeholders The system of e-learning education may seem very modern and cutting-edge as it uses the recent technology in the educational ecosystem. This does not imply, however, that it is in any manner beyond the reach of the common person or the exclusionary. Indeed, with the development of low-cost technology and the proliferation of internet connectivity and internet-enabled phones in even the most remote parts of the world, e-learning education system is becoming increasingly feasible in today's era. This is particularly crucial for marginalized communities that do not usually have access, infrastructure or the funding needed to construct and maintain traditional education systems. E-learning enables anyone with an internet connection and an internet-enabled device to sign up for a classroom that is revolutionary for learners who are often ignored or excluded from traditional learning systems. Easy to Scale Up Technology for the e-learning education system is built in such a way that there are continual improvement and development being done on the tools that support it. Whether it is a new version of an app with extra features or just advancing hardware, e-learning education system makes it easy for users to keep up with the times through easy patches or increasingly low-cost devices. This means that whether the school or college is small or large, it does make it easier to scale up to meet the present needs of the school when the e-learning education system has been implemented. Being able to easily update via a patch or software upgrade or having the rare hardware update also end up being cost-effective ensures that schools can scale up easily and stay up to date. Technology Embracing In the modern world, the use of technology is becoming ubiquitous. Entire jobs rely on it and there is no industry that has not been affected and embraced technology in some form of the other. It is important for schools and colleges to also prepare their children for this modern world by embracing the use of technology at the very earliest. The easiest and most beneficial way to do this would be through the implementation of e-learning education system, which ensures that students familiarise themselves with the use of various electronic or internet-enabled tools and platforms in their day to day lives, to perform their day to day tasks. Not only do students then become comfortable using technology, but they also understand the systems of thinking that underlie it making them natural learners in an increasingly technology embracing world. Lowered Overheads and Labor Cost Think of the endless overheads of running a school or college u2013 from simple things like pens and papers to storage space for all the physical records that need to be maintained. A traditional education system comes with massive overhead costs. E-learning on the other hand naturally eliminates many of these costs, since so many of the tasks and processes take place electronically. From classroom assignments being submitted using school management systems like Paatham to even the elimination of the need for a physical space to call a classroom, e-learning education system drastically reduces overhead costs for all stakeholders in the educational ecosystem. The same also applies to labor costs with a traditional education system. Many personnel is required to manage the logistical and temporal demands of a traditional classroom setting u2013 from study materials that are physical to the natural restrictions in the number of students that can be fit in a physical classroom. With e-learning education system such restrictions do not apply. Instead, since many tasks and processes are automated, the need for a human agent to perform them is eliminated resulting in downsizing and reduction in labor costs. This kind of reduction in costs is vital for budget-conscious industries such as education since valuable funds can then be redirected towards more worthy causes that would benefit all stakeholders in the educational ecosystem. Conclusion: Can e-learning replace traditional education systems? As we move into the future, it is likely that educators and management will continue to take advantage of the many benefits of e-learning systems. However, some classic traditional education system practices will remain. Rather than creating a false dichotomy where one is forced to choose between a traditional education system and e-learning it is more likely that a new form of systemic learning will emerge that is a blend of the two. We are already seeing this in practice u2013 with virtual classrooms becoming a reality thanks to tools like Paatham learning management system that allows for a seamless experience, for teachers to reach students in remote parts of the world, through massive online open courses through services. So while it is unlikely that the traditional education system will ever be completely eradicated, it will continue to evolve to be inclusive of new forms of technology and learning, via the e-learning education system.

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Artificial Intelligence and Machine Learning's Impact on Market Design

In complex environments, it is challenging to learn enough about the underlying characteristics of transactions so as to design the best institutions to efficiently generate gains from trade. In recent years, Artificial Intelligence has emerged as an important tool that allows market designers to uncover important market fundamentals, and to better predict fluctuations that can cause friction in markets. This paper offers some recent examples of how Artificial Intelligence helps market designers improve the operations of markets, and outlines directions in which it will continue to shape and influence market design. Mrs. Pushpalata S. Patil "Artificial Intelligence and Machine Learning's Impact on Market Design" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: https://www.ijtsrd.com/papers/ijtsrd14534.pdf Paper URL: http://www.ijtsrd.com/computer-science/artificial-intelligence/14534/artificial-intelligence-and-machine-learning's-impact-on-market-design/mrs-pushpalata-s-patil

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Machine Learning And its Applications in different Sectors

Machine Learning And its Applications in different Sectors Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being programmed. Machine Learning is used in situations where perfection is not expected, the goal is not to achieve predictions that are good enough to be useful. The value of machine learning technology has been recognized by companies across several industries that deal with huge volumes of data. Letu2019s have a look how some sectors / domains are implementing machine learning: Financial Services Companies in the financial sector are able to identify key insights in financial data as well as prevent any occurrences of financial fraud, with the help of machine learning technology. Usage of cyber surveillance helps in identifying those individuals or institutions which are prone to financial risk, and take necessary actions in time to prevent fraud. Usage of cyber surveillance helps in identifying those individuals or institutions which are prone to financial risk, and take necessary actions in time to prevent fraud. Marketing and Sales Companies are using machine learning technology to analyze the purchase history of their customers and make personalized product recommendations for their next purchase. ML helps to capture, analyze, and use customer data which helps to provide a personalized shopping experience and this is the future of sales and marketing. Government Government agencies like utilities and public safety have a specific need for ML, as they have multiple data sources, which can be mined for identifying useful patterns and insights. For example, sensor data can be analyzed to identify ways to minimize costs and increase efficiency. ML can also be used to minimize identity thefts and detect fraud. Healthcare ML is becoming a fast-growing trend in healthcare. Sensors in wearable provide real-time patient information, such as overall health condition, heartbeat, blood pressure and other vital parameters. The technology also empowers medical experts to analyze data to identify trends that facilitate better diagnoses and treatment. Transportation Transportation firms and delivery organizations are increasingly using machine learning technology to carry out data analysis and data modeling to make informed decisions and help their customers make smart decisions when they travel. Based on the travel history and pattern of traveling across various routes, machine learning can help transportation companies predict potential problems that could arise on certain routes, and accordingly advise their customers to opt for a different route. Oil and Gas Right from analyzing underground minerals and finding new energy sources to streaming oil distribution, Machine Learning applications for this industry are vast and are still expanding. This is perhaps the industry that needs the application of machine learning the most. By leveraging insights obtained from the data, companies are able work in an efficient manner to control costs as well as get an edge over their competitors. Visit http://gnexttechllc.com/ for Digital Marketing Company, Digital Advertising Company, SEO Service Provider, SEO Company, Social Media Marketing Company, Web Design Development Company, Web Design Company, Graphics Design Company, Software Company, Software Development Company, Mobile Apps Development Company.

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Artificial Intelligence (AI) company in USA and UK

Artificial Intelligence company in USA | Techsolvo Artificial Intelligence company in UK | Techsolvo https://techsolvo.com/artificial-intelligence-solution/ The world of technology u201cTechsolvou201d is the best Artificial Intelligence (AI) company in USA and UK. Techsolvo is the award-winning company and highly experience. We expert in Artificial Intelligence, Machine Learning, Internet of Things, Web, software, & Mobile Application development. Techsolvo is the listed of top AI company in USA or UK. visit www.techsolvo.com #Top Artificial intelligence company in USA #Top Artificial intelligence company in UK #Artificial intelligence company in USA and UK

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A Study on Google is an Artificial Encyclopedia Affecting Human Intelligence - An Empirical Study

Google is opening this platform to the world, which gives us an equal opportunity to peek in and see how the company thinks about developing machine learning systems. Internally, Google has spent the last five years building a massive platform for artificial intelligence and now they're unleashing it on the world. Although Google would prefer you call it machine intelligence they feel that the word artificial intelligence carries too many connotations and fundamentally they're trying to create genuine intelligence just in machine. The internet makes things faster, but faster is not always necessarily. Better we don't want to sacrifice our critical thinking and uniqueness for the attainment of a modest amount of additional productivity our cognitive thinking is one of our greatest possessions and we should take this extra time to preserve it. Prof. Rekha D. M | Sandhya G N "A Study on Google is an Artificial Encyclopedia Affecting Human Intelligence An Empirical Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27923.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/27923/a-study-on-google-is-an-artificial-encyclopedia-affecting-human-intelligence-u2013-an-empirical-study/prof-rekha-d-m

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Top 10 Applications Of Artificial Intelligence | Artificial Intelligence Applications | Simplilearn

Artificial intelligence (AI) is currently one of the hottest buzzwords in tech and with good reason. The last few years have seen several techniques that have previously been in the realm of science fiction slowly transform into reality. In this YouTube live session, let us look at some of the popular applications of Artificial Intelligence. Simplilearnu2019s Artificial Intelligence course provides training in the skills required for a career in AI. You will master TensorFlow, Machine Learning and other AI concepts, plus the programming languages needed to design intelligent agents, deep learning algorithms & advanced artificial neural networks that use predictive analytics to solve real-time decision-making problems without explicit programming. Why learn Artificial Intelligence? The current and future demand for AI engineers is staggering. The New York Times reports a candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S. (or Rs.17 lakhs to Rs. 25 lakhs in India) for engineers with the required skills. You can gain in-depth knowledge of Artificial Intelligence by taking our Artificial Intelligence certification training course. Those who complete the course will be able to: 1. Master the concepts of supervised and unsupervised learning 2. Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Comprehend the theoretical concepts and how they relate to the practical aspects of machine learning. 6. Be able to model a wide variety of robust machine learning algorithms including deep learning, clustering, and recommendation systems ud83dudc49Learn more at: https://bit.ly/2AlrLiB

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Demand for Compost Windrow Turning Machine Set for Stupendous Growth in and Post 2020, Buoyed by the Global COVID-19 Pan

Future Market Insightsu2019 recently published research study on the Compost Windrow Turning Machine market, titled u201cCompost Windrow Turning Machine: Global Industry Analysis, 2013-2017, and Forecast, 2018-2028u201d, offers a detailed value-volume analysis of the Compost Windrow Turning Machine market along with insights via. BPS analysis in (US$ Mn), on the basis of product type, output capacity and end-use industry. The volume analysis, for the Compost Windrow Turning Machine market, has been done in units (i.e. the number of Compost Windrow Turning Machines), covering data for the historical period ranging from 2013-2017 and forecasted up to 2028 with 2018 as the base year. In addition to the quantitative analyses provided by market size estimates and growth trends, the report on the global Compost Windrow Turning Machine market also provides qualitative analysis in the form of market dynamics, such as drivers, restraints, trends and opportunities, forecast factors, macroeconomic factors, porter's analysis, market definition and other factors, that will influence and impact the global Compost Windrow Turning Machine market. Sample of Research Report @ https://www.futuremarketinsights.com/reports/sample/rep-gb-4061 The report on the global Compost Windrow Turning Machine aims to provide insights with regards to market size and associated developments for the interested stakeholders. Marketing and business intelligence has been facilitated through information based on competition landscape, business strategies, technology roadmap and list of market participants, with relevant information on Compost Windrow Turning Machines. FMI has not only presented the research findings but also has added suitable recommendations and understanding of market dynamics which can be helpful for market entry, business development and sustenance in the market space. Compost turner Machine Market: Report Description For a complete understanding of the readers of the Compost Windrow Turning Machines in the best way possible, the report has been categorically divided into a multitude of categories on the basis of product type, output capacity and end use segment, on consolidated and by individual segments. The market estimates have been provided on global as well as regional levels. The first section of the Compost Windrow Turning Machine report includes market introduction/definition wherein product definition, taxonomy and market definition by segments have been analyzed and discussed. The market description also provides an outline of research limitations/ assumptions binding on the research study on the basis of which the entire framework has been devised. The next section of the global Compost Windrow Turning Machine market report discusses macroeconomic factors along with drivers, restraints, trends, value chain analysis and opportunities. This information has been backed up with suitable examples and facts as obtained from official and authentic data. In the subsequent section, the Compost Windrow Turning Machine market viewpoint has been covered, which includes the global value and volume analysis. Compost Windrow Turning Machine Market Segmentation: By Product Type Drum (Compost Windrow Turning Machine) Elevating Face (Compost Windrow Turning Machine) By Output Capacity < 500 cubic meters per hour 500 u2013 1000 cubic meter per hour >1000 cubic meter per hour By End Use Construction Industry (Compost Windrow Turning Machine) Agriculture Industry (Compost Windrow Turning Machine) Manufacturing Industry (Compost Windrow Turning Machine) By Region North America Latin America Western Europe Eastern Europe South East Asia & Pacific China India Japan Middle East and Africa The report provides significant information pertaining to the above-mentioned segments in the global Compost Windrow Turning Machine market. The last part in the market background includes a study of those factors that are expected to have an impact on the Compost Windrow Turning Machine market, such as technological growth, investments and other key insights pertaining to the market. A section dedicated to pricing analysis of Compost Windrow Turning Machines has been provided on the basis of product type on regional fronts. Weighted average selling price has been computed to arrive at the global average prices. The pricing analysis provides pricing by each configuration for the present scenario. Assumption and key considerations for the same have also been elucidated. The sections that follow consist of the global Compost Windrow Turning Machine market analysis by product type, output capacity, end use segment and region/country. The overall analysis of the Compost Windrow Turning Machine market begins with overall global market assessment, followed by analysis for numerous regions and a discussion on the macroeconomic environment in each particular region. Each regional section of the report contains qualitative data and quantitative aspects of the global Compost Windrow Turning Machine market. In the final section of the report, we have provided a competition analysis with company market share analysis pertaining to the Compost Windrow Turning Machines and performance of manufactures by tier down structure in the global Compost Windrow Turning Machine market. In the competition dashboard section of the global Compost Windrow Turning Machine market, we have provided a dashboard view of major players along with their market share and key business strategies. This would enable readers to evaluate strategies deployed by market leaders and help them develop effective strategies consequently. Sample of Research Methodology Report @ https://www.futuremarketinsights.com/askus/rep-gb-4061 Research Methodology The first stage of the research includes the formulation of a preliminary theory, which was considered from secondary as well as primary approaches. The subsequent steps involved triangulation of data collected using two different approaches. To determine market trends and opportunities, the global Compost Windrow Turning Machine market report has been segmented on the basis of four criteria: product type, output capacity, end use segment and region/country. For the final data analysis of the Compost Windrow Turning Machine market, we have considered 2018 as the base year and basic data was collected from public sources as well as other sources, such as the company annual reports, investor presentations and press releases, World Bank Statistics on revenue sales, newsletters, published reports on public domain, industry associationu2019s reports and paid databases on finance and corporate information. The collated data from the aforementioned sources was further validated from Compost Windrow Turning Machine manufacturers, end-user procurement agencies, distributors and regional representatives. ABOUT US: Future Market Insights is the premier provider of market intelligence and consulting services, serving clients in over 150 countries. FMI is headquartered in London, the global financial capital, and has delivery centers in the U.S. and India. FMIu2019s research and consulting services help businesses around the globe navigate the challenges in a rapidly evolving marketplace with confidence and clarity. Our customized and syndicated market research reports deliver actionable insights that drive sustainable growth. We continuously track emerging trends and events in a broad range of end industries to ensure our clients prepare for the evolving needs of their consumers. CONTACT US: Future Market Insights U.S. Office 616 Corporate Way, Suite 2-9018, Valley Cottage, NY 10989, United States T: 1-347-918-3531 F: 1-845-579-5705 Web: https://www.futuremarketinsights.com

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Mathematics For Machine Learning | Essential Mathematics - Machine Learning Tutorial | Simplilearn

Mathematics forms the core of Machine Learning and is one of the prerequisites. This presentation on Mathematics for Machine Learning will help you understand linear algebra, vectors, and matrices. Then, you will learn about integral calculus, followed by different topics in Statistics for machine learning. Finally, we'll look at Probability for Machine Learning. All these topics contain hands-on demo in Python. So, let's get started with Mathematics for Machine Learning. Data and its types Linear algebra and its concepts Calculus Statistics for machine learning Probability for machine learning About Simplilearn Machine Learning course: A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all peopleu2019s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning. What skills will you learn from this Machine Learning course? By the end of this Machine Learning course, you will be able to: 1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling. 2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems ud83dudc49Learn more at: https://bit.ly/3fouyY0

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Confusion Matrix In Machine Learning | Confusion Matrix Explained With Example | Simplilearn

A Confusion Matrix is an excellent metric to describe the performance of a classification model. This video on Confusion Matrix with Machine Learning will help you learn the basics of machine learning and the need for a confusion matrix. You will understand how to create a confusion matrix and how to create a confusion matrix. You will get an idea about the different metrics and perform a demo using logistic regression to find the model's accuracy. 1. Intro to Machine Learning 2. Type of Machine learning 3. Need for Confusion Matrix 4. What is Confusion Matrix 5. Creating a Confusion Matrix 6. Comparing Confusion matrix 7. 3x3 Confusion Matrix About Simplilearn Machine Learning course: A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all peopleu2019s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning. What skills will you learn from this Machine Learning course? By the end of this Machine Learning course, you will be able to: 1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling. 2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems ud83dudc49Learn more at: https://bit.ly/3fouyY0

4.76k views • 27 slides

Machine Glazed Paper Market to Witness Machine Glazed Paper, as Uncertainty Looms Following Global Coronavirus Outbreak

A recent market report published by Future Market Insights on the Machine Glazed Paper market provides global industry analysis for 2015-2019 & forecast for 2020-2030. The report offers a comprehensive assessment of the most important market dynamics. After conducting thorough research on the historical, as well as current growth parameters of the machine glazed paper market, the growth prospects of the market are obtained with maximum precision. Market Taxonomy The global machine glazed paper market is segmented in detail to cover every aspect of the market and present complete market intelligence to readers. Basis Weight u2022tUp to 40 GSM u2022t41 to 70 GSM u2022t71 to 100 GSM u2022tAbove 100 GSM Paper Type u2022tTissue Paper u2022tKraft Paper Grade u2022tUnbleached u2022tBleached Application u2022tBags & Pouches u2022tSacks u2022tWraps u2022tLabels & Release liners u2022tEnvelopes u2022tCoating & Lamination u2022tTrays, cups & bowls u2022tOthers (Gift Wrap) End Use u2022tFood & Beverages u2022tHealthcare u2022tElectrical & Electronics u2022tAutomotive u2022tPersonal care & Cosmetics u2022tTextile u2022tBuilding & Construction u2022tHousehold Regional Outlook u2022tNorth America (US, and Canada) u2022tLatin America (Brazil, and Mexico) u2022tEurope (Germany, UK, Russia, France, and Italy) u2022tSouth Asia (India, Indonesia, Thailand, Australia and New Zealand) u2022tEast Asia (China, Japan, and South Korea) u2022tOceania (Australia and New Zealand) u2022tMiddle East & Africa (MEA) (Turkey, GCC Countries, and South Africa) Report Chapters Chapter 01 u2013 Executive Summary The report begins with the executive summary of the machine glazed paper market, which includes a summary of the key findings and statistics of the market. It also includes dominant segments in the global machine glazed paper market, along with key facts about machine glazed paper market. It also includes key drivers and trends of the global machine glazed paper market. To Get the Sample Copy of Report visit @https://www.futuremarketinsights.com/reports/sample/rep-gb-7900 Chapter 02 u2013 Market Overview Readers can find detailed taxonomy and definition of the machine glazed paper market in this chapter, which will help them understand the basic information about machine glazed paper market present in the market. This section also highlights the inclusions and exclusions, which help readers to understand the scope of the machine glazed paper market report. Chapter 03 u2013 Key Market Trends It includes a comprehensive analysis of key trends such as product innovation and technological advancements that are impacting the global machine glazed paper market. Chapter 04 u2013 Global Machine Glazed Paper Market Demand Analysis (Volume u2019000 Tonnes) 2015-2019 and Forecast, 2020-2030 This section explains the global market volume analysis and forecast for the machine glazed paper market between the forecast period of 2020-2030. It includes the detailed analysis of the historical machine glazed paper market, along with an opportunity analysis for the future. Readers can also find the Y-o-Y growth opportunity for the forecast period (2020-2030). Chapter 05 u2013 Global Machine Glazed Paper Market u2013 Pricing Analysis This section highlights the average pricing analysis of basis weight (Up to 40 GSM, 41 to 70 GSM, 71 to 100 GSM and above 100 GSM) of machine glazed paper market in different regions across the globe. The weighted average pricing at the manufacturer-level is analyzed in this section. Chapter 06 u2013 Global Machine Glazed Paper Market Demand (Value in US$ Mn) Analysis 2015-2019 and Forecast, 2020-2030 This section explains the global market value analysis and forecast for the machine glazed paper market between the forecast period of 2020-2030. It includes the detailed analysis of the historical machine glazed paper market, along with an opportunity analysis for the future. Readers can also find the Y-o-Y growth opportunity for the forecast period (2020-2030). Chapter 07 u2013 Market Background This chapter explains the key forecast factors that are expected to influence the growth of machine glazed paper market over the forecast period. This chapter also highlights the key market dynamics of the machine glazed paper market, which include the drivers, restraints and opportunities. This section also includes value chain analysis. Chapter 08 u2013 Impact of COVID-19 This chapter explains how the COVID-19 has impacted the overall packaging industry. It also explains the impacts of COVID-19 on the key regions, current statistics and probable future impacts and current economic projections. Chapter 09 u2013 Global Machine Glazed Paper Market Analysis 2015-2019 and Forecast 2020-2030, by Basis weight Based on basis weight, the machine glazed paper market is segmented as Up to 40 GSM, 41 to 70 GSM, 71 to 100 GSM, and Above 100 GSM. In this chapter, readers can find information about key segments during the forecast period. Ask an Analyst @https://www.futuremarketinsights.com/ask-question/rep-gb-7900 Chapter 10 u2013 Global Machine Glazed Paper Market Analysis 2015-2019 and Forecast 2020-2030, By Paper type Based on paper type, the machine glazed paper market is segmented on the basis of tissue paper and kraft paper. In this chapter, readers can find information about key segments during the forecast period. so on.. About Us Future Market Insights (FMI) is a leading provider of market intelligence and consulting services, serving clients in over 150 countries. FMI is headquarters in London, the global financial capital, and has delivery centers in the US and India.FMIu2019s latest market research reports and industry analysis help businesses navigate challenges and make critical decision with confidence and clarity amidst breakneck competition. Our customize and syndicate market research reports deliver actionable insights that drive sustainable growth. A team of expert-led analysts at FMI continuously tracks emerging trends and events in a broad range of industries to ensure that our client prepare for the evolving needs of their customer Contact Us Mr. Abhishek Budholiya Unit No: AU-01-H Gold Tower (AU), Plot No: JLT-PH1-I3A, Jumeirah Lakes Towers, Dubai, United Arab Emirates MARKET ACCESS DMCC Initiative For Sales Enquiries: sales@futuremarketinsights.com For Media Enquiries: press@futuremarketinsights.com

128 views • 11 slides

Download Skim, Dive, Surface: Teaching Digital Reading (Teaching and Learning in Higher Education) | Ebook

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61 views • 5 slides

[EPUB] Deep Learning Full

[RECOMMENDATION] Deep Learning by Ian Goodfellow Free Copy Link Start here : https://bit.ly/310book Deep Learning Description An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors. PDF Download Deep Learning Free Collection, PDF Download Deep Learning Full Online, epub free Deep Learning,ebook free Deep Learning, free ebook Deep Learning ,free epub Deep Learning, online free Deep Learning , online pdf Deep Learning , pdf download Deep Learning , Read Online Deep Learning Book, Read Online Deep Learning E-Books, Read Deep Learning Online Free, Read Best Book Deep Learning Online,

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Bottle Labeling Machine

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Valid Google Professional-Machine-Learning-Engineer Study Plan, Professional-Machine-Learning-Engineer Mock Exams

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Artificial-Intelligence-Foundationブロンズ教材、Artificial-Intelligence-Foundation問題例

r u5f53u793eTech4Examu306eu8a2du7acbu4ee5u6765u3001u79c1u305fu3061u306fArtificial-Intelligence-Foundationu8a66u9a13u8cc7u6599u306bu5927u898fu6a21u306au4ebau6750u3001u8cc7u6599u3001u304au3088u3073u8ca1u6e90u3092u6295u5165u3057u3066u304du307eu3057u305fu3002u305du3057u3066u4ecau307eu3067u3001u79c1u305fu3061u306fu9593u9055u3044u306au304fu5168u4e16u754cu306bu7814u7a76u8cc7u6599u3092u7d39u4ecbu3057u3001u5e78u904bu3092u6c42u3081u308bu3059u3079u3066u306eu4ebau3005u3092u4f5cu308bu3068u3044u3046u5927u80c6u306au8003u3048u3092u6301u3063u3066u3044u307eu3059u3088u308au826fu3044u6a5fu4f1au306fu3001u5f7cu3089u306eu4ebau751fu306eu4fa1u5024u3092u5b9fu73feu3059u308bu305fu3081u306eu30a2u30afu30bbu30b9u6a29u3092u6301u3063u3066u3044u307eu3059u3002u3057u305fu304cu3063u3066u3001u5f53u793eu306eArtificial-Intelligence-Foundationu7df4u7fd2u554fu984cu306fu3001u8a66u9a13u306bu5408u683cu3057u3001u3088u308au826fu3044u672au6765u3092u52ddu3061u53d6u308bu306eu306bu5f79u7acbu3061u307eu3059u3002u307eu305fu3001u5e38u306bu5148u99c6u7684u306au7cbeu795eu3092u6301u3061u7d9au3051u3001u3042u306au305fu306eu9053u3092u6b69u3080u30d7u30edu30b8u30a7u30afu30c8u306bu7a4du6975u7684u306bu53d6u308au7d44u307fu307eu3059u3002r Tech4Examu306fu3001Artificial-Intelligence-Foundationu8a66u9a13u306bu30b9u30e0u30fcu30bau306bu5408u683cu3059u308bu306eu306bu5f79u7acbu3061u307eu3059u3002u6700u9ad8u306eArtificial-Intelligence-Foundationu5b66u7fd2u6559u6750u3078u306eu30c1u30e3u30f3u30cdu30ebu306bu3064u3044u3066u5fc3u914du3059u308bu5fc5u8981u306fu3042u308au307eu305bu3093u3002u591au304fu306eu53d7u9a13u8005u306fu3001u5f7cu3089u306eu52a9u3051u3092u63d0u4f9bu3059u308bu5bdbu5927u3055u3092u8cdeu8cdbu3057u307eu3059u3002u3053u308cu307eu3067u3001u3053u306eu5206u91ceu306eu4e3bu5c0eu7684u5730u4f4du306bu6311u6226u3057u305fu4ebau306fu3044u307eu305bu3093u3067u3057u305fu3002 APMG-Internationalu306eArtificial-Intelligence-Foundationu5b66u7fd2u30acu30a4u30c9u306eu5b58u5728u306fu3001u8a66u9a13u306bu5408u683cu3059u308bu52b9u7387u3092u9ad8u3081u308bu3082u306eu3068u898bu306au3055u308cu307eu3059u3002u5f53u793eu306fu3001u6642u9593u306eu7d4cu904eu3068u3068u3082u306bu3001u53d7u9a13u8005u304cu6700u592798u301c100uff05u306eu5408u683cu7387u3067u53d7u9a13u3067u304du308bu3088u3046u306bu306au308au307eu3059u3002u3059u3079u3066u306eu884cu52d5u306fu3001Artificial-Intelligence-Foundationu8a66u9a13u3067Foundation Certification Artificial Intelligenceu6210u529fu3059u308bu53efu80fdu6027u3092u5411u4e0au3055u305bu308bu3053u3068u3092u76eeu6307u3057u3066u3044u307eu3059u3002r >> Artificial-Intelligence-Foundationu30d6u30edu30f3u30bau6559u6750 <<r u8a8du5b9au3059u308bArtificial-Intelligence-Foundationu30d6u30edu30f3u30bau6559u6750u8a66u9a13-u8a66u9a13u306eu6e96u5099u65b9u6cd5-u30e6u30cbu30fcu30afu306aArtificial-Intelligence-Foundationu554fu984cu4f8br u3069u3093u306au696du754cu3067u81eau5206u306bu826fu3044u6607u9032u6a5fu4f1au304cu3042u308bu3068u5e0cu671bu3059u308bu8077u4ebau304cu3068u3066u3082u591au3044u3068u601du3063u3066u3001ITu696du754cu306bu3082u4f8bu5916u3067u306fu3042u308au307eu305bu3093u3002ITu306eu5c02u9580u8005u306fAPMG-Internationalu306eArtificial-Intelligence-Foundationu8a8du5b9au8a66u9a13u304cu3042u306au305fu306eu9858u671bu3092u52a9u3051u3063u3066u5b9fu73feu3067u304du308bu306eu304cu3088u304fu5206u304bu308au307eu3059u3002Tech4Examu306fu3042u306au305fu306eu5922u306bu5b9fu73feu3055u305bu308bu30b5u30a4u30c8u3067u3054u3056u3044u307eu3059u3002r APMG-International Foundation Certification Artificial Intelligence u8a8du5b9a Artificial-Intelligence-Foundation u8a66u9a13u554fu984c (Q32-Q37):r u8ceau554f # 32 In the 1800's the development of statistics led to___________theorem and is used in probabilistic inference.(Select the missing word.)r A. Boltzmann'sr B. Kolmogorov'sr C. The central limitr D. Bayes'r u6b63u89e3uff1aDr u89e3u8aacuff1aExplanationThe development of statistics in the 1800s led to the development of the Bayes' theorem, named after Reverend Thomas Bayes. This theorem is used in probabilistic inference, which is the process of using data to calculate the likelihood of a hypothesis or outcome. The theorem is used for determining the probability of an event occurring given its prior probability, as well as its associated conditions. The Bayes' theorem is also used in a variety of fields, such as machine learning, artificial intelligence, economics, and medical research.Sources:* BCS Foundation Certificate In Artificial Intelligence Study Guide: https://www.bcs.org/category/18071* APMGInternational: https://www.apmg-international.com/en/qualifications/qualification-resources/bcs-foundatio* EXIN: https://www.exin.com/en/certification/bcs-foundation-certificate-in-artificial-intelligencer u8ceau554f # 33 Collaboration, learning and iterative are terms used to describe what?r A. Waterfall projects.r B. Rapid software development.r C. Agile projectsr D. Trustworthy Al.r u6b63u89e3uff1aCr u89e3u8aacuff1aExplanationCollaboration, learning, and iterative are terms used to describe agile projects. Agile projects are designed to be adaptive and flexible, allowing teams to incorporate feedback and learn from their mistakes. This process encourages collaboration between team members, and emphasizes the importance of iterative development and continual improvement. Agile projects focus on delivering value quickly and efficiently, allowing teams to make changes and adapt to changing customer needs.References:[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-internationalr u8ceau554f # 34 What is one of the MAIN contributions of Al to the rapid development of The Fourth Industrial Revolution?r A. Enhanced design.r B. Big Datar C. Automationr D. Al personal assistants.r u6b63u89e3uff1aCr u89e3u8aacuff1aExplanationhttps://research.com/careers/what-is-the-fourth-industrial-revolutionArtificial Intelligence (AI) is playing a major role in the rapid development of the Fourth Industrial Revolution. AI technologies are enabling the automation of many processes that were previously carried out by humans or machines, which has greatly increased the speed, efficiency, and accuracy of these processes.Automation is one of the main contributions of AI to the Fourth Industrial Revolution, as it has greatly increased the productivity of businesses and industries, while reducing the cost of production and improving the quality of products.References: https://www.bcs.org/more/certifications/foundation-certificate-in-artificial-intelligence/ https://wwwr u8ceau554f # 35 If Al undertakes routine and monotonous tasks and takes these away from humans, what will humans do?r A. Leisure activitiesr B. Higher value work.r C. Sabotage the Al.r D. Change jobs.r u6b63u89e3uff1aBr u89e3u8aacuff1aExplanationAl is designed to take on routine and monotonous tasks, freeing up humans to take on more complex, higher value work. This can include tasks such as research, problem-solving, and decision-making. This shift in work roles is expected to increase productivity and efficiency, allowing humans to focus on more creative and innovative tasks. For example, robots can be used to automate mundane manufacturing processes, freeing up human workers to take on jobs that require more creative thinking and problem-solving.References:[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-internationalr u8ceau554f # 36 In Machine learning what are a brain's axons called?r A. Dendritesr B. Tetrahedra.r C. Edgesr D. Nodesr u6b63u89e3uff1aDr u89e3u8aacuff1aExplanationIn Machine Learning, the brain's axons are referred to as nodes. Nodes are the components of a neural network that are responsible for processing the input data and generating the output. A node is a mathematical function that takes input data, performs a computation on it, and produces an output. Each node is connected to other nodes in the network via edges, which represent the strength of the connection between the respective nodes. The strength of the connection between two nodes is determined by the weights assigned to each edge.The weights are adjusted during the training process to generate the desired results.For more information, please refer to the BCS Foundation Certificate In Artificial Intelligence Study Guide (https://www.bcs.org/upload/pdf/bcs-foundation-certificate-in-artificial-intelligence-study-guide.pdf) or the EXIN Artificial Intelligence Foundation Certification (https://www.exin.com/en/exams/artificial-intelligence-foundation).r u8ceau554f # 37......r 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