Best Python Libraries For Machine Learning


Best Python Libraries For Machine Learning

  • As you know python has a treasure of amazing and very powerful python libraries for Machine Learning, Artificial Intelligence, Data Science, and other specific tasks. According to data, There are over 137,000 python libraries and 198,826 python packages ready to ease developer’s regular programming experience. Here I’ll introduce the 7 Best Python Libraries For Machine Learning.
Machine Learning: Machine learning is a field of study that provides machines the ability to automatically learn and improve from experience without being explicitly programmed.

Amazing Python Libraries

  1. TensorFlow
  2. Numpy
  3. PyTorch
  4. SciPy
  5. Scikit-Learn
  6. Theano
  7. Keras
  8. Matplotlib

1. TensorFlow 

  • TensorFlow is a free and open-source software library for machine learning. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. TensorFlow is a symbolic math library based on data flow and differentiable programming.
  • Tensorflow has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications.

2. Numpy 

  • NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
  • NumPy offers mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms and plays well with distributed, GPU, and sparse array libraries. This is why Numpy is in the best Python libraries for machine learning.

3. PyTorch

  • PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab. It is free and open-source software released under the Modified BSD license. 
  • PyTorch is an open-source machine learning library for Python, based on Torch. It is used for applications such as computer vision and natural language processing. 


  • SciPy is a free and open-source Python library used for scientific computing and technical computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
  • The SciPy library is one of the core packages that make up the SciPy stack. It is fundamental library of scientific computing like NumPy.


  • Scikit-learn is one of the most useful libraries for machine learning in Python. It’s also known as sklearn.
  • Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines.

6. Theano

  • Theano is a Python library and optimizing compiler for manipulating and evaluating mathematical expressions, especially matrix-valued ones. In Theano, computations are expressed using a NumPy-esque syntax and compiled to run efficiently on either CPU or GPU architectures.
  • Another library which is very popular for machine learning and as well as in deep learning. Theano is a Python library that lets you define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).


  • Keras is an open-source software library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library. Up until version 2.3 Keras supported multiple backends, including TensorFlow, Microsoft Cognitive Toolkit, R, Theano, and PlaidML.
  • Keras is an open-source neural network library written in Python. (can also be used for machine learning) 

8. Matplotlib

  • Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+.
  • It is a comprehensive library for creating static, animated, and interactive visualizations in Python. we can plot 2D or 3D Graphs. Often mathematical or scientific applications require more than single axes in a representation. With this library, we can build multiple plots at a time.



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