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aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Your new Mentor for Data Science E-Learning.
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Toturials coming with the "data science roadmap" picture.
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
Probabilistic reasoning and statistical analysis in TensorFlow
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
Text and supporting code for Think Stats, 2nd Edition
Book_5_《统计至简》 | 鸢尾花书：从加减乘除到机器学习；上架！
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
A complete course for learning Bitcoin programming and usage from the command
Code repository for O'Reilly book
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
Quantitative analysis, strategies and backtests
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
Introduction to Statistics using Python
A library of metrics for evaluating recommender systems
scPerturb: A resource and a python/R tool for single-cell perturbation data
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
open source E-book on statistical physics