• Sheikh Aman

Top 6 Python libraries you should know for AI and Machine Learning.

Updated: Aug 10, 2020

What is the Python library?

Python library is generally a collection of different types of functions and methods, that allows you to perform many actions without writing your code.

What is the use of a Python library for AI and Machine Learning?

We all know Machine Learning and AI is one of the HOT topics in today's world. So, to get accurate as well as the quick results for our problem form Machine Learning and AI technology we need an extensive choice of tools, functions, and methods. All the libraries mentioned below provides all these facilities and gives the required output. We can assure that there is a great use of Python libraries for AI and Machine Learning.

TOP 6 Pyhton Libraries are:-

TensorFlow was developed by Google's Brain team for their use only. In November 2015, under Apache license 2.0 it was released to the public. It runs on CPUs, GPUs, TPUs(Tensor Processing Unit - a chip built with Tensorflow).

It is basically a free and open-source software library used for differential programming. It is one of the most popular math libraries used by machine learning applicants and neural networks.

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       2. Keras

This library is mainly designed for deep neural networks and its features like modular, extensible and user-friendly making it perfect for beginners. It can also run on top of TensorFlow and libraries like Theano, PlaidML.

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This library is perfect for evaluating and manipulating matrix calculation as well as a mathematical Expression. It is highly used for fast numerical computations. It can also run on both GPU and CPU. It is built on top of Numpy, Theano is tightly integrated with Numpy.

It helps to perform intensive data computations up to 140x faster.

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It is an open-source and free library developed by Facebook and released under the modified BSD license. This is a deep learning library used for an application like computer vision and natural language processing. It can create accurate computational graphs that can be changed even during runtime due to its robust and seamless framework.

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It is a free machine learning library designed on python language, that features a supervised and unsupervised learning algorithm. It gives results like classification, clustering and regression algorithm like K- means, gradient boosting and random forest.

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This library is becoming popular day by day. Developer builds high-level data structure which is intuitive as well as seamless with the help of pandas library. Methods available is pandas are data filtering, grouping, combing etc.are

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