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Jürgen Hermann edited this page Apr 6, 2019
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- Foundations of Machine Learning (Bloomberg)
- Designing Data Intensive Applications and its related books
- How to Learn Machine Learning, the Self-Starter Way
- Python Machine Learning Tutorials – Real Python
- A curated list of awesome Machine Learning frameworks, libraries and software
- Machine Learning Courses by Andrew Ng
- jakevdp/PythonDataScienceHandbook – “Python Data Science Handbook” with the full text in Jupyter Notebooks.
- hangtwenty/dive-into-machine-learning – Dive into Machine learning with Jupyter notebooks and scikit-learn.
- jupyter4edu/jupyter-edu-book – A Handbook for teaching and learning with jupyter.
- Natural Language Processing with Python – Analyzing Text with the Natural Language Toolkit (free e-book)
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- Jupyter – Project Jupyter exists to develop open-source software, open standards and services for interactive computing across dozens of programming languages.
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The Python Graph Gallery⎋ – Visualizing data with Python (includes source snippets).
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Seaborn – A Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
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Bokeh – An interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics, and to extend this capability with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.
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