9 Reasons Why You Should Keep Learning Machine Learning

1. 9 Reasons Why You Should Keep Learning Machine Learning Machine Learning is an application of Artificial Intelligence. It allows software applications to become accurate in predicting outcomes. Machine Learning focuses on the development of computer programs, and the primary aim is to allow computers to learn automatically without human intervention. Google says “Machine Learning is the future,” and the future of Machine Learning is going to be very bright. As humans become more addicted to machines, we’re witnesses to a new revolution that’s taking over the world, and that is going to be the future of Machine Learning. More online businesses are integrating machine learning into their operations, with the bigger and established ones trailblazing the revolution. Machine learning has brought myriad opportunities and improved strategies to help business owners foster customer relationships and get more profit and conversions. If you haven’t fully leveraged the power of machine learning in your business, let me give you five reasons why you should do so now. 1. Machine learning helps increase your efficiency. Can you imagine buying from the grocery store without having to wait in line to pay for your goods?

2. If you can’t, then you’d better prepared because that is now a reality. Amazon, for one, has applied machine learning to make grocery shopping ultra-efficient for your customers through computer vision, sensor fusion, and deep learning algorithms. Using the Amazon Go app, customers only need to open it, scan the QR code when they enter, pick their items, and confidently walk out of the store. Amazon Go detects the items they take out from the shelves, automatically adds them into their virtual carts, and charges the bill into their Amazon accounts when they leave. Such is a classic example of how machine learning can increase the efficiency of your business operations and processes, and help your customers, too. While you can use pre-built machine learning technologies, you can also master how to develop them yourself. The concept may sound complicated, but through the right machine learning course, you can invest in building machine learning technologies that suit your specific business needs. 2. You can understand your customers better. Since the launch of automation, businesses have embraced customer- centeredness. If you want to maintain a competitive edge over other businesses, you need to know what your customers need and give it to them. If you fail to do so, you can lose your potential customers to your competitors. Here is where machine learning plays a critical role.

3. Machine learning can analyze and organize patterns, trends, and data about your customers’ demographic profiles, choices and preferences, behaviors, and others. Machine learning can get these data from online tools and mechanisms that you use, such as emails collected from sign-ups. Such ability by machine learning enables you to know and understand your customers more quickly. For instance, for your advertising campaigns on Google Adsense or other channels to be effective, they should be deeply targeted according to the mentioned data. The more accurately you can understand your customers and their needs and wants, the more sharply you can target your ads. 3. You can personalize your marketing campaigns. When customers feel that your offers are accurately aligned with their preferences — or personalized — they are more likely to patronize your business. The question now becomes, how do you personalize your campaigns and customer shopping experience? The answer is by using machine learning to build them based on the data gathered and analyzed, just like Flybits does. Flybits is a context-as-a-service product that helps businesses provide hyper-personalized digital content and experiences for your customers. With its easy user interface, your digital marketers can easily and instantly access internal and external data through cloud synchronization.

4. Its real-time mobile analytics allow you to customize your content and campaigns for your customers according to their location, weather, and others. What’s more, Flybits ensures your customers’ data are safe and kept confidential. Your customers retain full ownership over their data as well. Personalized campaigns are influential in increasing your conversions and sales, and machine learning help you create them. 4. Machine learning recommends products to your customers. In line with personalizing your campaigns, machine learning can recommend products similar to what you previously viewed, purchased, or added to your cart. Amazon is one company that uses machine learning to recommend similar products. Machine learning picks up on the features of the items you previously searched, viewed, or bought, and creates algorithms from those data. Amazon then personalizes its recommendations to you by stating your name and showing similar items. It can also recommend to you similar items that other customers viewed or bought. Let’s say you clicked on some Omine grey loafer sneakers. Machine learning notes the features of the shoes, such as color, size, and style, and then shows you what other customers also bought. In this way, they leverage social proof and fear of missing out (FOMO) to entice you to consider buying what other customers also liked (besides widening your range of options).

5. That said, machine learning helps you improve your sales and conversions significantly. 5. Machine learning helps to detect fraud. The convenience that online payment systems offer, especially through mobile applications, has attracted both customers and businesses to transact and purchase online. However, transmitting money online has also attracted cybercriminals and given them opportunities to execute fraudulent attacks. Some businesses have implemented different cybersecurity measures but find that they need more to stop fraud. If you’re experiencing the same problem, there’s fortunate news for you. Machine learning can now help strengthen businesses’ fraud detection system. For instance, PayPal uses machine-learning mechanisms to catch suspicious and shady transactions and separate them from legitimate ones. Machine learning further assists you by inspecting specific attributes among your data and develop standards as the basis for examining each transaction. Machine learning, therefore, helps prevent malicious transactions from taking place even before you can complete them. 6) Learning machine learning brings in better career opportunities According to a Tractica Report, AI driven services were worth $1.9 billion in 2016 and are anticipated to rise to $2.7 billion by end of 2017 of which 23% of the revenue comes through machine learning technology.

6. A report from TMR mentions that MLaaS (Machine learning as a Service) is expected to grow from $1.07 billion in 2016 to $19.9 billion by end of 2025. Machine learning is the shining star of the moment. With every industry looking to apply AI in their domain, studying machine learning opens world of opportunities to develop cutting edge machine learning applications in various verticals – such as cyber security, image recognition, medicine, or face recognition. With several machine learning companies on the verge of hiring skilled ML engineers, it is becoming the brain behind business intelligence. Netflix announced prize worth $1 million to the first individual who could enhance the accuracy of its recommendation ML algorithm by 10%. This is a clear evidence on how significant even a slight enhancement is in the accuracy of recommendation machine learning algorithms to improve the profitability of Netflix. Every customer- centric organization is looking to adopt machine learning technology and is the next big thing paving opportunities for IT professionals. Machine learning algorithms have become the darlings of business and consumers so if you want to put yourselves somewhere in the upper echelon of software engineers then this is the best time to learn ML. 7) Machine Learning Engineers earn a pretty penny The cost of a top, world-class machine learning expert can be related to that of a top NFL quarterback prospect. According to SimplyHired.com, the average machine learning engineer salary is $142,000.An experienced machine learning engineer can earn up to $195, 752. 8) Machine Learning Jobs on the rise “You need a special kind of person to build a hammer, but once you build it, you can give it to many people who will use it to build a house.”

7. The major hiring is happening in all top tech companies in search of those special kind of people (machine learning engineers) who can build a hammer (machine learning algorithms). The job market for machine learning engineers is not just hot but it’s sizzling. According to the popular job portal Indeed, the number of open machine learning jobs have been steadily rising from 2014 to the onset of 2016, from 60 job postings per million to more than 100. The number of job postings jumped up to 150 postings per million by end of 2016. Indeed job trends report also reveals that the number of machine learning engineer job postings outstrip the number of searches for machine learning jobs – 100 million searches vs. 150 job postings. A recent survey on the Indian job market found that there is a requirements of 4000 machine learning engineers in Bengaluru alone. Here is a snapshot of the total number of machine learning jobs in US for IT professionals as of November 13, 2017 – Machine Learning Engineer Jobs Positions on Glassdoor.com – 12000+ 9) Machine learning is linked directly to Data Science Machine learning appears as a shadow of data science. Machine learning career endows you with two hats, one is for a machine learning engineer job and the other is for a data scientist job. Becoming competent in both the fields makes an individual a hot commodity to most of the employers. It means that you can analyse tons of data, extract value and glean insight from it, and later make use of that information to train a machine learning model to predict results. In many organizations, a machine learning engineer often partners with a data scientist for better synchronization of work products. Furthermore, data scientist has been voted the Sexiest Job of 21st Century so one can get started as a data scientist specializing in Machine Learning and become more desirable to employers.

8. If these reasons ring a bell then you might be interested to get your start in machine learning career right now. Are you ready to learn machine learning and land your dream job at one of the top tech companies? Share your personal approach, knowledge, and strategy in the comments below. Everyone has a different take on machine learning, and we want to know your thoughts. Future of Machine Learning Machine Learning can be a competitive advantage to any company be it a top MNC or a startup as things that are currently being done manually will be done tomorrow by machines. Machine Learning revolution will stay with us for long and so will be the future of Machine Learning. Resources to learn Machine Learning Learn Artificial Intelligence for Beginners Machine Learning In The Cloud With Azure Machine Learning Machine Learning Python: Regression Modeling MACHINE LEARNING with Microsoft AZURE Machine Learning with AWS Machine Learning from scratch through Python Machine Learning and Training Neural Network in MATLAB Practical Deep Learning: Image Search Engine DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS Machine Learning and Data Science using Python for Beginners Machine Learning using R and Python

9. Machine Learning Adv: Support Vector Machines (SVM) Python Conclusion We have studied the future and the algorithms of Machine Learning. Along with that, we have studied its application, which will help you deal with real life. Furthermore, if you have any queries, feel free to ask in the comments section.