Awesome List Updates on May 07, 2023

6 awesome lists updated today.

1. Awesome Ironsworn

Mary Wootters. Randomized Algorithms and Probabilistic Analysis. Stanford - Key tools of probabilistic analysis, and application of these tools to understand the behaviors of random processes and algorithms. Emphasis is on theoretical foundations, though applications will be discussed in machine learning and data analysis, networking, and systems. Topics include tail bounds, the probabilistic method, Markov chains, and martingales, with applications to analyzing random graphs, metric embeddings, and random walks.

Koutsoupias. Probability and Computing. Oxford - Introduction to probabilistic methods in computer science.

Harvey. First and Second Course in Randomized Algorithms. Columbia. - Respectively, undergrad and grad courses for probabilistic methods in algorithms.

Lee. Randomized Algorithms and Probabilistic Analysis. Washington. - Topics include Discrete probability, High-dimensional geometry and statistics, Information and entropy, and Markov chains and convergence to equilibrium.

Substation (⭐373) - Substation is a cloud native data pipeline and transformation toolkit written in Go.

The Node Way (⭐1.5k) - An entire philosophy of Node.js best practices and guiding principles exists for writing maintainable modules, scalable applications, and code that is actually pleasant to read.

Achieving 4000x Speedups with PureJaxRL - A blog post on how JAX can massively speedup RL training through vectorisation.