Maximum Entropy Methods Tutorial

Learn the fundamentals of maximum entropy methods through this comprehensive tutorial series taught by Professor Simon DeDeo. Explore how maximum entropy principles help understand probability distributions when working with limited information or constraints. Master the theoretical foundations through an introduction to maximum entropy concepts, then apply these methods to practical examples including the classic taxicab problem. Dive deeper into real-world applications by modeling complex systems such as open source software ecosystems and analyzing historical pricing data from Sears-Roebuck catalogs. Progress through twelve structured modules that build from basic concepts to advanced applications, including step-by-step walkthroughs of maximum entropy calculations and their interpretations. Gain hands-on experience with constraint-based modeling techniques that are widely used in physics, economics, ecology, and data science for making optimal predictions under uncertainty.

Syllabus

Maximum Entropy Tutorial: Intro To Max Ent
Maximum Entropy Methods Tutorial: A Simple Example: The Taxicab
Maximum Entropy Methods Tutorial: The Maximum Entropy Method
Maximum Entropy Methods Tutorial: MaxEnt applied to Taxicab Example Part 1
Maximum Entropy Methods Tutorial: MaxEnt applied to Taxicab Example Part 2
Maximum Entropy Methods Tutorial: Review Of Max Ent
Maximum Entropy Methods Tutorial: Modeling the Open Source Ecosystem 1
Maximum Entropy Methods Tutorial: Modeling the Open Source Ecosystem 2
Maximum Entropy Methods Tutorial: Modeling the Open Source Ecosystem 3
Maximum Entropy Methods Tutorial: Modeling Sears-Roebuck Prices 1
Maximum Entropy Methods Tutorial: Modeling Sears-Roebuck Prices 2
Maximum Entropy Methods Tutorial: Conclusion