awesome-scientific-python
github.com/rossant/awesome-scientific-python ↗A curated list of awesome scientific Python resources
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Installation instructions →What's inside
Lists of libraries
- A gallery of interesting Jupyter Notebooks
- A Primer on Scientific Programming with Python
Hans Petter Langtangen, Springer, 2014, 872 pages.
- CME 193, Introduction to Scientific Python
Stanford University, Sven Schmit, 2015.
- Coursera Data Science with Python
University of Michigan.
- Deep Learning with Python
François Chollet, Manning, 2017, 384 pages.
- edX Foundations of Data Science: Computational Thinking with Python
UC Berkeley, Ani Adhikari, John DeNero, David Wagner.
Other scientific libraries
- AltairData visualization
Declarative visualization in Python.
- BokehData visualization
Interactive visualization for the web.
- bqplotData visualization
2D interactive visualization in Jupyter.
- CaffeNeural networks
Deep learning framework.
- CuPyGPU computing
NumPy-like library with CUDA.
- CythonCompilation
Combine C and Python
Domain-specific libraries
Core libraries
- Getting started with SciPySciPy
- IPythonIPython/Jupyter
Interactive Python computing in the terminal.
- JupyterIPython/Jupyter
Open interactive computing in many programming languages.
- JupyterLabIPython/Jupyter
Next-generation web-based interactive programming and computing environment.
- Jupyter NotebookIPython/Jupyter
Web-based environment for interactive computing.
- matplotlibmatplotlib
Showing a sample of 129 resources. View the full list on GitHub →