While Torch’s makers call it the easiest ML framework, its complexity is relatively simple that comes from its scripting languages interface. The programming language is full of numbers that are not categorized by numbers like any other language.
There are some big giants of corporates who are using Torch nowadays like Facebook AI research group, IBM, Yandex, Idiap Research Institute, etc.
It is created with C++ but it can be used with other languages as well like Java, Python, Ruby, C#, etc. This tool is curated for large scale learning. Mainly, it focuses on Kernel machines like support vector machines and classification and regression problems.
This one is the most popular tool for every ML specialist. This tool implements data flow graphs where data can be processed by a series of algorithms described by the graph.
Tensorflow contains a large amount of documentation, training materials, and online resources. Besides, Google has long term plans for Tensorflow through third-party developers.
Theano is the Python library that allows you to define, optimize and evaluate mathematical expressions involving multi-dimensional array efficiently. You can easily integrate this tool with NumPy, dynamic C code generation, and symbolic differentiation.
Microsoft Azure Machine Learning Studio is a collaborative tool that can be used to build, test and deploy predictive analytics solutions on your data. This tool publishes models that can be used as web services.
Accord is a .Net machine learning framework developed to build production-grade computer vision, computer audition, signal processing and statistics application. This well-documented framework makes audio and image processing simpler. Accord.Net can be used for numerical optimization, artificial neural networks, and visualization.
Another scalable machine learning library that runs on Hadoop. Several algorithms are included here like naive Bayes, generalized linear regression, K-means and many more.
So now you know how you can implement AI and Machine Learning modules with the open-source networks. If you think we have missed out on any popular Open Source network that our viewers must know about, do let us know in the comment section.
We will come soon with some trending topics that are being cooked for you. Till then, stay upskilled!
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