Machine Learning with Python

Getting into Machine Learning and AI is not an easy task. Many aspiring professionals and enthusiasts find it hard to establish a proper path into the field, given the enormous amount of resources available today. The field is evolving constantly and it is crucial that we keep up with the pace of this rapid development. In order to cope with this overwhelming speed of evolution and innovation, a good way to stay updated and knowledgeable on the advances of ML, is to engage with the community by contributing to the many open-source projects and tools that are used daily by advanced professionals

Top 6 Python Machine Learning Open Source Projects (2016)

Tensorflow has moved to the first place with triple-digit growth in contributors. Scikit-learn dropped to 2nd place, but still has a very large base of contributors.

Compared to 2016, the projects with the fastest growth in number of contributors were

1. TensorFlow, 169% up, from 493 to 1324 contributors
2. Deap, 86% up, from 21 to 39 contributors
3. Chainer, 83% up, from 84 to 154 contributors
4. Gensim, 81% up, from 145 to 262 contributors
5. Neon, 66% up, from 47 to 78 contributors
6. Nilearn, 50% up, from 46 to 69 contributors

Also new in 2018:

1. Keras, 629 contributors
2. PyTorch, 399 contributors

For more details visit this link :

 Top 20 Python Machine Learning Open Source Projects (Nov 2016)