Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

DuckDB is an analytical in-process SQL database management system

The fundamental package for scientific computing with Python.

SciPy library main repository

NumPy aware dynamic Python compiler using LLVM

The Sphinx documentation generator

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

Edit, preview and share mermaid charts/diagrams. New implementation of the live editor.

Panel: The powerful data exploration & web app framework for Python

The Missing Semester of Your CS Education 📚

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Open-source scientific and technical publishing system built on Pandoc.

ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.

A computer science textbook

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

STUMPY is a powerful and scalable Python library for modern time series analysis

The machine learning toolkit for time series analysis in Python

This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.

Feature engineering package with sklearn like functionality

🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟𝗘 & 𝗠𝗟𝗢𝗽𝘀 for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

A Tutorial for Setting Python Development Environment with VScode and Docker

Software Design by Example: a tool-based introduction with Python

Compendium of free ML reading resources

A pythonic python wrapper around FFTW

Awesome Panel supports Panel and its users. We want to show how awesome the framework is and help push it forward. ❤️🐍📈

In which I put together my thoughts on the practice of data science.

Nvidia contributed CUDA tutorial for Numba

Pythonic class-based interface to LLMs

📈 Machine Learning from the perspective of a Statistician using R