The Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and sustainably. The process is documented in this repo.

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference,…

Introducción a Python y análisis exploratorio de datos

📚 A curated list of papers for Software Engineers

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

FastAPI framework, high performance, easy to learn, fast to code, ready for production

Data Analysis Baseline Library

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

Awesome Privacy - A curated list of services and alternatives that respect your privacy because PRIVACY MATTERS.

The fundamental package for scientific computing with Python.

https://huyenchip.com/ml-interviews-book/

scikit-learn sprint docs

Official Repository for Code associated with 'Practical Natural Language Processing' book by O'Reilly Media

Adversarial Threat Landscape for AI Systems

The fastai book, published as Jupyter Notebooks

Git Intro Tutorial

PyTorch code for "Adaptively-Halting Policy Network for Early Classification", published at KDD'19. Paper link: https://thartvigsen.github.io/papers/kdd19.pdf

Presentacion del Workshop de la eko

A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI )

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

A game theoretic approach to explain the output of any machine learning model.

BAyesian Model-Building Interface (Bambi) in Python.

A collection of Bayesian data analysis recipes using PyMC3

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 ;)

A python tutorial on bayesian modeling techniques (PyMC3)

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

Latex code for making neural networks diagrams