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Top 10 Machine Learning Software

https://techvidvan.com/tutorials/machine-learning-softwares/

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Top 10 Machine Learning Software

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  1. Top 10 Machine Learning Software Techvidvan

  2. T O P 1 0 M A C H I N E L E A R N I N G S O F T W A R E A M O N G L E A R N E R S A N D P R O F E S S I O N A L S In this article, we will be looking at the top software for Machine Learning. Machine learning is a type of artificial intelligence that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values. These software are great for running your ML code. There are countless numbers of software and tools in the industry. We will be looking at popular ones among both learners and professionals. It will provide you with all the information about Machine Learning software and tools. Techvidvan

  3. 1. TensorFlow Tensorflow is a free and open-source tool for Machine Learning. It is a cloud-based platform that allows users to create and run ML algorithms or models. It is often used across a variety of tasks but features a particular specialization in training and inference of deep neural networks. 2. Apache Mahout Apache Mahout, a project of the Apache Software Foundation to supply free implementations of distributed or otherwise scalable machine learning algorithms focused totally on algebra. 3. Apache Singa Apache SINGA is an Apache top-level project for developing an open-source machine learning library. It provides a versatile architecture for scalable distributed training, is extensible to run over a good range of hardware, and features a specialization in healthcare applications. Techvidvan

  4. 4. Amazon Machine Learning (AML) Amazon Machine Learning is known to be a robust, cloud-based service that creates it easy for developers of all skill levels to use machine learning technology. This section introduces the key concepts and terms which will assist you understand what you would like to try to make powerful machine learning models with Amazon ML. 5. Accord.NET Accord. Net, as the name suggests, is a .NET machine learning framework. The framework comprises a set of libraries that are available in source code as well as via executable installers and NuGet packages. It is an extension of AForge.NET. It offers libraries on image and audio processing which are written in C# language. 6. Shogun Shogun is a great platform that offers great libraries, and algorithms for ML problems. It’s written in the C++ language. Shogun is a Machine Learning software that provides interfaces in R, Python, JAVA, Ruby, etc. It is not very popular among professionals. But it is among the students. It offers APIs for algorithms that are easier to manage.

  5. 7. Google Cloud ML Engine This platform helps to work with complex algorithms and large data. Google provides a cloud- based platform for ML app developers and data scientists to train and run their models. It is usually used by companies and enterprises for faster response to client emails. 8. PyTorch Pytorch is a Facebook-developed platform. It provides a great framework for Deep Learning and neural networks. It is very useful for building, testing, and running your own research prototype. PyTorch also promotes distributed training. It means you can do parallel work. It can access more than one GPU at a time. This allows it to take large input in less time. 9. Keras Keras is an open-source neural network library. It is written in Python and it can run on top of other high-level software like TensorFlow, CNTK, and Theano. This Machine Learning software helps in the fast experimentation of various models and algorithms. It also provides support for CNN (Convolutional Neural Network) and recurrent networks.

  6. 10. H2O.ai H2O.ai is a company whose aim is to make ML easier for everyone. They offer various ML products like H2O, sparkling water, Deepwater, steam, and driverless AI. H2O allows users to switch between Python, R, and other tools. This allows us to use the best tool for the project. It also provides a front-end tool called flow. Flow helps you to play with datasets and work on them. H2O has platforms and versions like H2O-3, H2O4GPU, etc. These provide support to convolutional neural networks and recurrent networks.

  7. Summary From this TechVidvan’s Machine Learning Softwares article, we learned about the various software, platforms, and libraries. We also learned about software that supports various models. We also looked at software that helped in modeling and rapid prototyping. Techvidvan

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