Open Source Software for Machine Learning

With the help of machine learning systems, we can examine data, learn from that data and make decisions. They will allow the software to become more accurate in predicting outcomes without being explicitly programmed. So, the idea over here, model or algorithm is used to get data from the world and the data is being fed back into the model where it can improve overtime when it comes to machine learning software. Also, this software can be used for the future growth of the country. Below is the open-source software for machine learning.

TensorFlow

GitHub - tensorflow/tensorflow: An Open Source Machine Learning ...

This is an open-source network for the framework which is easy to use and has many platforms. TensorFlow is known for the well-maintained and widely used frameworks for machine learning. Also, it was created by Google for supporting its research and production objectives and used by many companies that include Dropbox, eBay, Intel, Twitter, and Uber. Even the TensorFlow allows developing neural networks using flowgraphs.

Keras

Keras is the open-source programming library that is designed to create deep learning models. Well, this is written in python and can be deployed on Al technologies such as TensorFlow, Microsoft Cognitive Toolkit and Theano. Keras is known for the user-friendless, modularity and ease of extensibility.

Scikit Learn

A Flask API for serving scikit-learn models - Towards Data Science

This is the open-source library developed for machine learning and code is written in Python. It has several features like classification, regression, clustering and dimensionality reduction.  Also, it has other open-source projects like Matplotlib, NumPy and SciPy where it focuses on data mining and data analysis. Scikit learn is best to use in machine learning software.

Pytorch

The torch is a machine learning library that offers a wide range of algorithms for deep learning. This open-source framework provides you with the speed and flexibility when handling the machine learning projects without causing unnecessary complexities in the process. So, it is written using the scripting language Lua and comes with an underlying C implementation. Torch includes N-dimensional arrays, linear algebra routines and numeric optimization routines that support iOS and android platforms.

The above-mentioned tools are best to use in machine learning software for implementing the algorithm in various fields. Hope that I have covered all the topics in my article about open source software for machine learning. Thanks for reading!

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