This project is a curated knowledge repository providing theoretical guides, practical challenge banks, and professional handbooks for technical interview preparation in data science and machine learning. It serves as a comprehensive study resource that combines theoretical knowledge with algorithmic practice. The repository features specialized study resources including a probability and statistics handbook, a machine learning reference for algorithms and neural network architectures, and a coding and SQL challenge bank designed to simulate recruitment assignments. It also includes a technic
Notebooks for the third edition of Think Stats
Reproducing examples from the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman with Python and its popular libraries: numpy, math, scipy, sklearn, pandas, tensorflow, statsmodels, sympy, catboost, pyearth, mlxtend, cvxpy. Almost all plotting is done…
The main features of empathy87/the-elements-of-statistical-learning-python-notebooks are: Mathematics and Statistics.
Open-source alternatives to empathy87/the-elements-of-statistical-learning-python-notebooks include: alexeygrigorev/data-science-interviews — This project is a curated knowledge repository providing theoretical guides, practical challenge banks, and… allendowney/thinkbayes2 — by Allen B. Downey. allendowney/thinkstats — Notebooks for the third edition of Think Stats. amitkaps/hackermath — ― Richard Feynman. camdavidsonpilon/probabilistic-programming-and-bayesian-methods-for-hackers — This project is a computational statistics textbook and Bayesian data analysis course. It serves as a guide for… fastai/numerical-linear-algebra — This project is a comprehensive library for numerical linear algebra and scientific computing, designed to provide…
