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written in Jupyter Notebook
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Learn how to design, develop, deploy and iterate on production-grade ML applications.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
The fastai book, published as Jupyter Notebooks
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
Notebooks for learning deep learning
Repo for the Deep Reinforcement Learning Nanodegree program
Resources for "Natural Language Processing" Coursera course.
Solution for https://www.coursera.org/learn/language-processing
libardolara / watson-studio
Forked from cicenet/wsWatson Studio Hands-On using features of data wrangling, AutoML, and Jupyter Notebooks.