Machine Learning is one of the most trending technologies today with businesses, big and small, coming forward to invest in it; primarily to prevent/avoid risks, make informed decisions and grow faster. When leveraging ML techniques and algorithms, enterprises generally use either Python or R. Furthermore, most ML courses and tutorials also use one of these two programming languages.
Python has been around for a while and is being used for quite a lot of purposes other than Machine Learning, including backend development, desktop app development, advanced computing etc. R, on the other hand, is primarily used by statisticians and data miners. Both languages also come with all-inclusive ML libraries.
With TensorFlow, ML models can be built and trained easily as the library supports a number of activation functions, network layers, optimizers and various other components. It also features GPU support and is praised for its performance.
You might have guessed from the name by now that natural has something to do with natural language processing which is closely associated with machine learning. natural is a library for NLP with Node.js.
Licensed under MIT, the open source library supports Tokenization, strings matching, sentiment analysis, phonetic matching and more.
Feedforward neural networks, vector machines support, Naïve Bayes, decision trees etc. are just a few of the supervised learning methods supported by the popular open source library.
Unsupervised learning methods include principal component analysis, cluster analysis, self-organizing maps etc.