Julia
- Introduction to Julia
- Julia Data Science [book]
- Statistics with Julia [book]
- Introduction to Computational Thinking (MIT course)
- Julia Programming Language Twitter Community
- Julia Language Slack workspace/community
- Julia Programming YouTube channel
- Pluto.jl: simple reactive notebooks for Julia
- IJulia: a Julia-language backend combined with the Jupyter interactive environment
- Julia-sublime: Julia language support for Sublime Text 4 or above
- Plots.jl: data visualization in Julia (get started)
- Agents.jl: a pure Julia framework for agent-based modeling (ABM) (the zombie outbreak example)
- Javis.jl: Julia Animations and Visualizations
- Flux.jl: the elegant machine learning stack
- Turing.jl: Bayesian inference with probabilistic programming
- Julia for Economists Bootcamp, 2022
Python
- Google’s Intro to Python class
- Python Data Science Handbook [book]
- Project Jupyter: interactive computational environments for Python, R, Julia, ..
- Colab: Jupyter notebook environment in the cloud (get started)
- binder: turn a Git repo into a collection of interactive notebooks
- Style guide for Python code (PEP 8)
- GitBook: a command line tool (and Node.js library) for building beautiful books using GitHub/Git and Markdown (or AsciiDoc).
- NumPy for MATLAB users guide
- Python performance tips
- Scipy Lecture Notes
- A curated list of Python frameworks, libraries, software and resources
- Anaconda, a Python distribution platform
- Matplotlib: Visualization with Python
- Seaborn: Statistical Data Visualization
- Bokeh: a Python Interactive Visualization Library for Modern Web Browsers
- Pandas: Python Data Analysis Library
- GeoPandas: working with geospatial data in Python easier.
- pandas-gbq: wrapper for Google’s BigQuery analytics web service to simplify retrieving results from BigQuery tables using SQL-like queries
- Scikit-Learn: Machine Learning in Python
- NTLK: Natural Language Toolkit
- SpaCy: Natural Language Processing in Python and Cython
- Gensim: Topic Modeling for Humans
- TextBlob: Simplified Text Processing
- TensorFlow: An end-to-end open source machine learning platform
- PyTorch: An open source machine learning framework that accelerates the path from research prototyping to production deployment
- Automatic Forecasting Procedure
- adjustText: a small library to help you adjust text positions on matplotlib plots
- flask, web development one drop at a time
- Django: a high-level Python web framework
Data Science
- Elements of Statistical Learning: Data Mining, Inference, and Prediction [book]
- An Introduction to Statistical Learning with Applications in R [book]
- Pattern Recognition and Machine Learning [book]
- Deep Learning [book]
- Dive Into Deep Learning [book]
- Gaussian Processes for Machine Learning [book]
- Bayesian Methods for Hackers [book]
- Reinforcement Learning: An Introduction [book]
- Econometrics Notes: Elements of Linear Algebra, Statistical Analysis, and Econometric models
- Advanced Data Analysis from an Elementary Point of View [book]
- Intro to Probability for Data Science [book]
- Python Data Science Handbook [book]
- A Curated List of Machine Learning Frameworks, Libraries and Software sorted by Language
- Loss Data Analytics: An open text authored by the Actuarial Community
- Frequentism and Bayesianism: A Python-driven Primer
- Statistics Done Wrong
- Best Practices for Scientific Computing
- Geospatial Data Science [course]
- Bayesian Learning [course]
Network Science
- A First Course in Network Science [tutorials]
- Network Science [book]
- NetworkX, a Python software package for the creation, manipulation, and study of complex networks
- iGraph, a collection of network analysis tools with the emphasis on efficiency, portability and ease of use
- Graph-tool, an efficient Python module for manipulation and statistical analysis of graphs
- SNAP, Stanford Network Analysis Platform
- LightGraphs.jl, a platform for network and graph analysis in Julia
- netrd: A library for network {reconstruction, distances, dynamics}
- Gephi, the open graph visualization platform
- Mark Newman’s Network Datasets
- Stanford Large Network Dataset Collection
- APS Data Sets for Research
- Social Media Focal Events: tools for organizing data collected around focal events on social media
Data Visualization
- Plotly: interactive charts and maps for Python, R, Julia, ggplot2, .NET, and MATLAB
- R-Shiny, an R package to build interactive web apps
- D3.js (by Mike Bostock)
- NVD3.js, re-usable charts for d3.js
- Sigma.js, a JavaScript library dedicated to graph drawing
- Chart.js, simple, clean and engaging charts for designers and developers
- Leaflet.js, an open-source JavaScript library for mobile-friendly interactive maps
- pyLDAvis: Python library for Interactive Topic Model Visualization
- mpld3, a D3.js viewer for Matplotlib (by jakevdp)
- Harvard’s CS171 Visualization Course