Open Source projects have always led innovation in the technology sector. A good example is the contribution of the Python programming language to the evolution of machine learning.
Here are the best open source projects developed in Python.
Google’s open source library for machine learning offers a wide range of features. Google has developed it to meet the need to build and train neural networks. The library assists with the detection, deciphering of images and correlation, such as teaching and understanding applied by humans.
Keras is another open source neural network library developed using Python. He is able to work in Deep Learning, TensorFlow and Theano. Initially, it was designed to enable fast experiments with deep neural networks.
This library offers a wide range of algorithms needed for supervised learning and unsupervised learning via the Python interface. Scikit-learn offers distributions for several versions of Linux.
This is one of the oldest and most popular frameworks written in Python. Django was originally designed to help developers create fast web applications. The framework facilitates the rapid creation of websites with as few resources as possible.
The micro-frame designed with Python is suitable for web development. The framework does not impose a specific solution for each task, but suggests several personalized or third-party decisions with personal consideration.
It is the most powerful web library and open source toolkit, multifunctional and flexible. The package is suitable for different types of data, that is, ordered and unordered. Pandas helps analyze and structure data for Python
Tornado is a scalable, unblocked Web server and framework for web applications. The framework was created for high performance.
The framework is designed and developed by the Kivy organization, a cross-platform open source software for mobile application development. The library is compatible with Android, Linux, iOS, Windows and OSX. You can use multiple Kivy elements to create multiple applications.