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Today I Learned about Data Science…

Online Resources

Training Materials

• 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

Books

• 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)

Articles / Blog Posts

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Other Resources

• /r/datascience Wiki

Productivity & Tools

• Jupyter – Project Jupyter exists to develop open-source software, open standards and services for interactive computing across dozens of programming languages.

Data Analysis

• NumPy
• SciPy
• Pandas

Visualization

• The Python Graph Gallery⎋ – Visualizing data with Python (includes source snippets).

• Financial Times Visual Vocabulary⎋

• The Graphic Continuum (by Visual.ly)⎋

• Seaborn – A Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.

• 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.

Artificial Intelligence

Machine Learning*