Machine learning and software development make up a large part of all the open-sources projects created with the help of Python. In recent years, these projects caused the creation of many working places for programmers interested in open-source development. Naming the most popular such open-source projects written in Python, it is necessary to mention TensorFlow, Keras, Scikit-learn, Flask, Django, Tornado, Pandas, Kivy, matplotlib, and the Requests.
Popular Open Source Projects In Python
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.
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.
Scikit-learn is the library that provides an 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 academic use of Scikit-learn.
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.
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.
Tornado is a scalable, non-blocking web server and framework for web applications. 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’ requests.)
Pandas is one of the most powerful open-source, multifunctional, and flexible web libraries and a toolkit providing data analysis and data structures for Python. This Python package is well suited for different types of data ordered and unordered, Arbitrary matrix data, and statistical data sets.
Kivy is the main framework developed by the Kivy organization. A cross-platform free open-source software for mobile app 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.
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 project fosters the development of an 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.