1. TensorFlow TensorFlow is an open source software library for machine learning of a wide range of tasks. The library is developed by Google to meet its needs in systems that can build and train neural networks to detect and decrypt images and correlations, similar to the teachings and understandings applied by people.
  2. Keras Keras is an open source neural network library coded in Python and capable of working on the basis of such software as Deep learning, TensorFlow, and Theano. It was initially designed to enable fast experiments with deep neural networks. The Keras main focus is on being modular, user-friendly, and extensible. Also, read: Best Python Tools For Machine Learning And Data Science
  3. Scikit-learn Scikit-learn is the library which provides the immense range of algorithms for Supervised Learning and Unsupervised Learning through the interface for the Python programming language. This library is distributed under the “Simplified BSD License” and has distributions for many different Linux versions, thereby encouraging the commercial and the academic use of Scikit-learn.
  4. Django Django is one of the most popular frameworks created for Python. Django was designed to help developers create web applications as quickly as possible. Creation means the formation of ideas, the development, and the release of the project. With Django web development goes fast with fewer resources at each stage. Thus, it can be called an ideal solution for developers for whom the deadline issue is a top priority.
  5. Flask Like Django, Flask is an accurate micro framework suitable for a variety of web development tasks. It has a very large community and many modules for all occasions. Unlike Django, Flask does not impose a specific solution for each task the programmist might face. Instead, it suggests using various third-party or custom decisions on your personal consideration.
  6. Tornado Tornado is the scalable, non-blocking web server and framework for web application. It was created for high performance and is one of the web servers able to withstand the C10k problem (the problem of handling a large number of clients’ request.)
  7. Pandas Pandas is one of the most powerful open source, multifunctional, and flexible web library and a toolkit providing data analysis and data structures for the Python. This Python package is well suited for different types of data ordered and unordered, Arbitrary matrix data and statistical data sets.
  8. Kivy Kivy is the main framework developed by the Kivy organization. A cross-platform free open-source software for mobile apps developing. The library is applicable to be run on Android, OS X, Linux, IOS, and Windows. This framework contains many elements for building various applications.

Conclusion

All the above-mentioned open-source projects are much more than just about coding stuff. The creators of the open-source machine-learning software and software development, take into account the whole chain of benefits and consequences of using their code in the future. Taking into account that every such a project fosters the development of open-source environment, it must be said that nowadays Python makes a significant contribution to the technical progress of multifunctional data libraries. These popular Python open source projects maintain the concept of the transparent experience share among the open-source community.