Ashish Yadav
Python is one of the most popular programming language for Machine Learning Projects. And on the other side, Machine Learning is a leading field in the 21st century. To grasp machine learning or Artificial Intelligence, you need to know complete python programming. Python Programming is used in Machine Learning, Deep Learning and
Artificial Intelligence is becoming popular day by day. Python programming is a simple and easy programming language.
In this article, We are going to introduce the Top 10 Most Popular Python Libraries for Machine Learning. We have listed the best Python libraries for machine learning for beginners. If you want to be a master of machine learning then you will have to learn these python libraries, so let’s start.
1. Pandas
Pandas is mainly used for data analysis, which is one of the most popular Python libraries. Pandas library is developed for extracting and organizing data and it also offers built-in functions and methods to the group, combine, and filter datasets. Data can be prepared, loaded, manipulate and analyze with the panda’s library. Pandas library has powerful data frames, flexible data handling, and low-level python libraries. Some of the features of Pandas Library are:- Aggregations, Visualizations, Concatenations, Iteration and Sorting, etc.
Developed by Wes Mckinney
Launched in – 2008
Written in Python, C, and Cython
2. NumPy
NumPy stands for Numerical Python used to process the python NumPy array and support n-dimensional arrays. NumPy Library is used to handle linear algebra and Fourier series transformations. NumPy is used by Tensorflow and other libraries for their internal calculations. NumPy has many built-in functions for numerical routines that make it so popular. Some of the features of Numpy Libraries are:- Easy to use and interact, Enhances performance, Has a large community of programmers and Manages garbage collection, etc.
Developed by Travis Oliphant
Launched in – 2005
Written in Python, C, and Cython
3. Scikit-Learn
Scikit Learning is one of the best Python machine Learning Libraries for building Machine Learning Algorithms. It was first introduced as a third-party extension to the Scipy Library. Scikit Learn Library can be used to build machine learning models because it contains a large number of tools for predictive modeling and analysis. Some of the features of Scikit Learning Libraries are:- contains massive potential algorithms, fast community support, etc.
Developed by David Cournapeau
Launched in – 2007
Written in– Python, C++, and Cyhton
4. Matplotlib
Matplotlib is one of the best python libraries used for data visualization. It is used to draw patter or graphs because it offers lots of features and tools controlling line style, font properties, and many more. It is one of the top machine learning libraries to explore. You can create Bar Charts, Error Charts, Histograms and scatter plots, etc. The main use of Matplotlib is Data Visualization and plotting.
Developed by– Michael Droettboom et al
Launched in – 2003
Written in– Python
5. SciPy
SciPy stands for Scientific Python which is an open-source python library. SciPy is used in Scientific computing and mathematical functions derived from NumPy. There are many features of the SciPy Library, as it-is-easy to use the library, fast computational power, and improved computations. SciPy Python Library is used for Scientific computation and technical computing. Some Features of SciPy are Fast Fourier transform, image optimization, linear algebra, etc.
Developed by– Community library project
Launched in – 2001
Written in– Python, C++, C, and Fortran
6. TensorFlow
TensorFlow is one of the most popular Machine Learning Libraries based on neural networks. TensorFlow was created by the Google Brain research team in 2015 to use in google. But after some time it started to gain a lot of popularity among big companies and now it is one of the top python machine learning libraries. TensorFlow is an
open-source library used for numerical computation and it runs and trains neural networks. TensorFlow uses a multidimensional array known as tensors and can perform multiple operations on specific inputs.
Developed by– Google Brain team of Google
Launched in – 2015
Written in– Python, CUDA, and C++
7. PyTorch
The PyTorch library is one of the largest machine learning libraries that was designed and developed by Facebook’s AI Research Lab. PyTorch is used for computer vision, natural language processing(NLP), and many others,s, etc. It is suitable for machine learning and deep learning beginners because it supports a lot of features and tools. Some Features of PyTorch are beginner-friendly, custom data loader, and multi-GUI support.
Developed by Facebook’s AI Research lab
Launched in – 2016
Written in– Python, CUDA, and C++
8. Theano
Theano is one of the speediest machine learning libraries used for scientific computing, mathematical expression, and matrix calculation. Theano Library provides tools that execute, define and optimize mathematical models and expressions with multidimensional arrays. Theano is also used to detect and diagnose various types of errors. Theano has fast execution speed, optimized stability and it is one of the top machine learning libraries to explore. Developed by– Montreal Institute for Learning Algorithms (MILA), University of Montreal
Launched in – 2007
Written in– Python, CUDA
9. Seaborn
Seaborn is a Python data visualization library that is based on Matplotlib. Seaborn provides a high-level interface for drawing informative and attractive statical graphs. Seaborn is more comfortable than another library with drawing statical graphs. It has customizable themes and provides data visualization with a sense of design.
Developed by Michael Waskom
Launched in – 2007
Written in– Python, CUDA
10. Keras
Keras is one of the best machine learning libraries used to create deep learning models, especially neural networks. Keras is based on TensorFlow and Theano librariesCognitive ToolKit. Some main features of Keras are Supports multi-backend, is flexible and easy to utilize, Works similarly on CPU and GPU, etc.
Developed by François Chollet (original), various (present)
Launched in – March 2015
Written in– Python
Conclusion:
So we have listed the Top 10 Most Popular Python Libraries for Machine learning for beginners. This library is mostly used in Machine learning, deep learning, and artificial intelligence.
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