Download
1 / 6
60 likes | 71 Views
Artificial intelligence has facilitated the processing and use of data in the business world. With the growth of AI and ML, data scientists and developers now have more AI tools and frameworks to work with. We believe it's important for machine learning platforms to be easy to use for business people who need results, but also powerful enough for technical teams who want to push the boundaries of data analysis with customizable extensions. The key to success is choosing the right AI framework or machine learning library.
E N D
Artificial intelligence has facilitated the processing and use of data in the business world. With the growth of AI and ML, data scientists and developers now have more AI tools and frameworks to work with. We believe it's important for machine learning platforms to be easy to use for business people who need results, but also powerful enough for technical teams who want to push the boundaries of data analysis with customizable extensions. The key to success is choosing the right AI framework or machine learning library. What is an AI Framework? AI frameworks provide the necessary components to efficiently build, train, test, and deploy models. Start with the basics if you want to learn advanced AI techniques and work in the field. Prioritizing learning AI frameworks will help you build AI applications development faster than starting from scratch with algorithms. The need for AI and ML has increased tremendously. Additionally, the community has grown, leading to the development of AI strategy frameworks that significantly simplify learning AI. Top 10 Artificial Intelligence Tools and Frameworks
Now, let's discuss several AI tools and frameworks that you should be aware of. Have a look. 1. PyTorch As one of the open-source machine learning (ML) frameworks, PyTorch was developed and introduced by none other than Facebook, the leading social media giant. The tool is the right choice for building deep learning models and has gained great popularity due to its flexibility and ease-of-use attributes. The AI framework is popular for its computational graph that allows developers to change the architecture of the network on the fly. PyTorch has the largest community of users who contribute to its development. Whether it is natural language processing or computer vision, you can use this framework for various applications. Recommended To Read: Application of Computer Vision in Artificial Intelligence 2. TensorFlow It is another open-source ML framework being developed by the leading search engine Google. It includes the ability to support a variety of machine learning algorithms and is also appropriate for everyone, whether they are new or experienced users. You can install this frame more easily. The framework also enjoys having the largest community and is perfect for use in various applications, be it natural language processing, image recognition, speech recognition, and many more. 3. Keras
Based on Python, Keras is a high-grade neural network and the best choice for beginners who want to quickly prototype and also want to experiment with deep learning models. The framework provides good support for Theano and TensorFlow as back-end engines and offers a user-friendly interface for building neural networks. You can use this framework for image classification, natural language processing, and speech recognition. Recommended To Read: The Business Case for AI in HR 4. Scikit-Learn Scikit-Learn is the right choice for all those beginners looking for the famous Machine Learning library for Python. Whether it's regression, classification, or clustering, the frameworks offer a variety of ML algorithms. It is an easy-to-use AI framework and provides a complete set of tools for data preprocessing and model evaluation as well. You can use this tool for a variety of purposes, be it customer segmentation, fraud detection, or sentiment analysis. 5. Theano If you are looking for an open-source numerical computing library for Python, Theano may be your right choice. It is the best choice for building deep learning models and offers a variety of tools for developing and training neural networks. The framework is popular for its efficient implementation of the matrix operation, which makes it perfect, especially for large-scale competitions. 6. OpenCV It is another open-source computer vision library that offers numerous tools for video and image processing. It offers excellent support for different video and image formats and provides different features for
object recognition, feature detection, image segmentation, and many more. Recommended To Read: Cost to develop a voice assistant app 7. Caffe Developed by Berkeley AI Research, Caffe is another popular deep learning framework. It is most widely used in the development of convolutional neural networks (CNNs) and is also popular for its fast execution time. The framework includes numerous tools for developing and training neural networks and also provides support for GPU and CPU computation. You can use Caffe for image classifications, semantic segmentation, and object detection. 8. MxNet MxNet is another AI framework that is built with scalability in mind. Provides full support for multi-machine and multi-GPU training. The framework includes many features, including easy writing of custom layers in higher-level languages. As a community-developed framework, MxNet is available with TVM support, increasing implementation support. 9. OpenNN OpenNN is another robust AI framework that includes extensive analytics that is suitable for both beginners and experienced programmers. It comes with a tool like Neural Designer, which is one of the most popular tools for sophisticated analysis. The tool has the ability to offer tables and graphs to analyze the data entered. Recommended To Read: Natural language processing in ai example 10. CNTK
It is another open-source AI framework that is a fast and highly flexible neural network that allows messages, texts, and also speech training. It also provides the ability for quick evaluation of machine models while taking care of correctness and accuracy, making it a suitable setup for scaling. It includes an easy-to-use and aggressive design. Apart from this, its integration with crucial massive data sets makes it a perfect choice for use by many leading brands including Skype and many others. What are the characteristics of AI frameworks? The main purpose of using an AI framework is to simplify the AI application development process. AI frameworks are available with numerous features, which makes them more useful. Let's discuss some of the features of AI frameworks here. • Data processing is one of the features of the AI framework. Using data processing tools, developers can clean, ingest, and preprocess data. The tool helps developers to convert the data into a more suitable form. The tool includes several libraries for feature engineering data, disputes, and data visualization. • The AI framework includes more libraries for developing ML models. These types of libraries include several pre-built models for various common tasks, such as NLP, image recognition, speech recognition, and more. It also provides the most suitable tools for model training, optimization, and validation. • The AI framework is also available with various tools that help developers implement various machine learning models. It also includes several other tools, including model serving platforms, cloud-based deployment, and more. Recommended To Read: Benefits of artificial intelligence in lms platforms
• Performance optimization is another crucial feature of the AI framework. The framework includes several tools for the performance optimization of ML models. The tool also includes algorithms for pruning, model compression, and quantization. The framework also includes the tools to optimize the execution of different models on particular hardware architectures. Conclusion Companies that have realized the potential of AI in their businesses early on have been able to reach greater heights. AI not only drives the business but also makes it more efficient in a short period. The AI trend in businesses can be compared to the digital process that was introduced to take the pain out of paper processes. This revolution brought a major change, similarly, AI will also bring a major change in all industries. You can master AI tools by enrolling in the best USM, artificial intelligence development company in New York . Intellipaat provides systematic learning with real-time projects and case studies. At the center of this shift are AI-powered tools that help businesses focus on efficiency and find better ways to drive revenue. However, a Herculean task that companies must undertake is to find the right AI tools based on their needs. The right AI tool can help companies make huge leaps in terms of cost savings and increased bottom-line profits.
