Resources

Consider this a public bookmark bar. These are resources I've found useful or think might be one day.

Disclaimers: still in progress, definitely not comprehensive, links may not work, and in no particular order.

I welcome any additions, suggestions, or corrections! Feel free to create a pull request or send me an email.

I've found a good portion of this from links other folks have shared on Twitter. Thanks, y'all. Also a very big thank you to everyone who created the original content.

Table of Contents

• Python
• R
• GitHub
• AMPL
• Julia
• Other languages
• General coding
• Math prog. software
• Math prog. resources
• Operations research-adjacent material
• Data viz
• Datasets
• Communication
• Healthcare
• Jobs and summer schools
• Funding
• Teaching
• Anti-racism
• Blogs I like (and read occasionally)
• Various advice
• Eclectic

Python

• Overview
  • Whirlwind tour from @jakevdp
  • Overview from @drvinceknight
  • Scipy lecture notes
    • Getting started
  • Targeted
    • Python for Mathematicians (drvincekinght)
    • Python for Epidemiologists (pzivich)
• Free Textbooks
  • Think Python by @AllenDowney, beginners guide, programming exp. not necessary
  • Python Data Science Handbook by @jakevdp
  • Intro to Machine Learning in Python by @amueller
  • Bayesian Methods for Hackers (Pilon)
  • Modeling and Simulation in Python by @AllenDowney, targeted towards intro undergrads
• Community
  • Slack channel to learn data science in Python
• Overall tutorial
  • Python Software Foundation
• Topics/packages
  • Pandas (data processing)
    • Beginner tutorial from @gjreda
    • Intermediate tutorial from @tomaugspurger
  • Networks
    • Package: NetworkX
      • Tutorial: network analysis using humanities data
      • Tutorial: Chinese postman problem
      • Network simplex
    • Package: SNAP
      • Analysis of graphs and networks
      • Claims often faster and able to solve larger problems than NetworkX
  • Simulation
    • Discrete-event
      • Package: SimPy
        • Google group
        • Book chapter by Barry Nelson
      • Package: Ciw (for open queueing networks)
    • Agent-based modeling
      • Package: Mesa, general purpose
        • Tutorial
      • Package: ABCE, economic modeling
  • List of operations-research-related packages
  • Optimization
    • Overview (Ted Ralphs)
    • Modeling languages
      • Package: gurobipy
        • Walk-through of building simple model
        • Walk-through of semi-complex model
        • Example models
          • List
          • Guided tour
      • Package: PuLP, linear programs
      • Package: Pyomo, all-purpose
        • How to run models
        • Example models
      • Package: Pysp, extends Pyomo for stochastic programming
    • Solvers & algorithms
      • Package: scipy.optimize
      • Package: CVXPY, convex opt
        • Short-course
      • Package: Optimist, SDDP in water systems
      • Package: PyBnB, parallel branch-and-bound
      • Package: StochOPy, stochastic optimization
      • Package: StOpt, stochastic control (written in C++, Python bindings)
      • Package: py-lapsolver, fast linear assignment problems
      • Package: munkres, Hungarian algorithm
      • Library: PyMaxFlow, Max flow/min cut
      • Package: PyPSA, power systems analysis
      • Package: PySCIPOpt
        • Book
    • Plot convex hull
    • Examples
      • Optimization tutorial (ekhoda)
      • TSP
        • Implement TSP, Video
        • A few algos tutorial (Norvig)
      • Genetic algo (Stoltz)
      • Facility location problems (SCIP)
  • Dimensionality reduction
    • Package: umap, uniform manifold approx. and projection
  • Game theory (source)
    • Software: Gambit
    • Package: Nashpy, 2-player games/compute equilibria, paper
    • Package: Axelrod, iterated prisoner's dilemma
    • Package: PyNFG, network form games
    • Library: lrslib, lrsnash can be used to compute Nash equilibria
    • Within SageMath, games: cooperative with finite players; matching; normal form with N players
  • Math
    • SageMath textbook: Computational Mathematics with SageMath, Zimmermann et al.
  • Machine learning
    • Flowchart, choosing the right estimator
    • Sklearn tutorial from @jakevdp
    • Checklist before releasing (Almeida)
  • Statistics
    • Package: lifelines, survival analysis
  • Supply chain
    • Package: Supplychainpy
  • Webscraping
    • Tutorial (by Agarwal)
  • Convert PDF to html
    • Package: PDFMiner, then can be used to parse
  • Other fields
    • Package: CobraPy, biological network modeling - constraints/optimization
    • ChemE code, optimize process simulators
  • Visualization / figures
    • Python Graph Gallery - lots of examples wit