Python which is the most popular language of 2019 has an insane number of libraries. Python is considered as the most versatile programming language because it has many libraries for each problem out there and yet many developers are creating new libraries so they could also contribute to growing python. Here in this article, we have mentioned the top 10 Python libraries which are heating up the developer community and trending topic likes AI, ML, Data Science and lots more.

What are Python Libraries:

Python libraries are those python files which contain pre-written code so you can grab that pre-written code and use it in yours, this increase the code reusability.

Top Python Libraries:

TensorFlow

TensorFlow

Machine Learning is not a hype anymore it’s the reality of future and future is all about Artificial Intelligence and Machine Learning. TensorFlow is the most popular library that is used to build Machine learning Models.

It is an end-to-end open source library and many other programming languages also support this library because of the increasing popularity of Machine Learning. It is developed by Google and Google use this library to build their AI models.

TensorFlow can store an algorithm in a cube and array-like structure and perform a tensor operation on them. Even in the neural computation developers using TensorFlow because it is very good with the new algorithms.

TensorFlow features:

  • It is an open source library
  • With TensorFlow, we can develop ML models very easily because it uses high- level APIs.
  • It can create models for different platforms
  • It comes with a simple and flexible architecture.
  • It has a large expert community.

Pandas

Pandas

It is a Data Analysis library, which mostly used for data science applications. It is an open source library and by far counts under the most famous libraries of python, it has a large community across the globe who are using this library to create new projects.

This Library also used to create Machine learning Models because of its data handling features, this library uses high-level structure and many algorithms to analyze the data. Even developers this library to sort complex data.

Pandas Features

  • Provides High Performance
  • Easy to use the library
  • It has many built-in methods
  • It also provides a graphical interface

NumPy

NumPy

NumPy is also one of the most famous python libraries if you are a python intermediate developer you must have heard of this library because this library provides one of the most basic Data Structures that every high-level programming language should have.

Python does not have built-in array Data Structure though it has Data Structure called list which looks similar to an array but, it does not perform all the operations that an array supposed to do. Apart from the array it also provides many mathematical functionalities like matrix (which is also a part of the array).

NumPy Features:

  • This library has good documentation
  • Provides many mathematical functionalities to python
  • It is very easy to learn
  • Play a very vital role in Data Science 

SciPy:

SciPy

SciPy is similar to NumPy with some distinction, though NumPy and SciPy both support many common features yet we use SciPy when we deal with a large number of data and stats.

SciPy commonly uses for data science using Python, it is also an open source-library with huge community support. Basically, it is a collection of many mathematical algorithms but it is specifically used to solve statistics problem. There are many other libraries which are used for data science but SciPy is the simplest amongst them.

SciPy Features:

  • Large community support
  • Rapid development
  • Simple data science tool
  • Easy to get started

Keras:

Keras

It is an open source and High-level neural Network python library that commonly used for Deep learning algorithms and experiments. This library is written in Python itself which make it capable of running on the top of other Machine learning libraries used by python. Keras also use Theano and TenserFlow at the backend to perform many tasks. The main drawback of Keras is its speed as compared to other machine learning libraries it is quite slow that why developers do not consider this library for their projects.

Keras Features:

  • It has many features like compiling models, processing data-sets, visualization of graphs, and much more.
  • It provides a modular approach to our models
  • It is completely based on python that’s why it is easy to debug

Theano

theano

It is also a powerful python library which is used for machine learning, Deep learning, and data analysis. It has many mathematical algorithms and it also comes with multi-dimensional array support which can be used for complex data.

Theano Features

  • It can integrate with NumPy
  • It can perform many complex mathematical functions.
  • It can evaluate expression faster as compared to other python’s machine learning libraries 

Scikit-Learn

Scikit-Learn

Another library which is well known for Machine learning and Data Science. When it comes to a huge amount of data and complex data then developer considered this library to handle that. This library comes with many built-in algorithm and training methods like regression. This library is built using NumPy, SciPy and matplotlib libraries that explain the Data handling power of this library.

Scikit-Learn Features

  • It has many inbuilt methods for cross-validation.
  • It is a very powerful library for Unsupervised learning Models.
  • It also provides the graphical interface 

Matplotlib

Matplotlib

This library is used to provide a graphical interface to the user. Matplotlib basically used with NumPy and SciPy libraries because the main job of this library is to plot 2D graphs for various filtered data. First, we use the NumPy and SciPy or any other data analysis library to sort the data then we use this library so we could get a proper graphical view of that data. This library helps to analyze the data in a fun way so even a non-programmer person can also read the data.

Matplotlib Features

  • Help to plot a graphical interface for the generated data.
  • This library is fun to use
  • It can plot various kind of graphs like a bar graph, a pie graph and lots more
  • This library is very easy to learn

Pygame

Pygame

If you want your python skill to make games, you can use python PyGame library. PyGame library is used to build games for the windows and Linux platforms, though this library cannot be used to make 3D games, for an intermediate developer who wants to increase his python skill can use this library to make fun games.

PyGame features:

  • It has good documentation
  • You can create 2D games
  • It has a low learning curve

Request:

Requests

Request library is the most useful library for python frameworks. Approximately, every python web framework uses this library to send a request to the HTTP server. The request library helps us to send organic HTTP request without any manual changes.

Request Features:

  • International Domains and URL’s
  • Keep-Alive & connection pooling
  • A session with cookie Persistence
  • Browser-style SSL verification

Conclusion:

Here in the above article, we have mentioned python top 10 libraries and mostly pertained on Data Science, Artificial Intelligence, Machine Learning, and Deep Learning because these fields have a more promising future as compare to others.

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