Lists (22)
Stars
21 Lessons, Get Started Building with Generative AI
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Examples and guides for using the OpenAI API
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Google Research
This repository provides tutorials and implementations for various Generative AI Agent techniques, from basic to advanced. It serves as a comprehensive guide for building intelligent, interactive A…
A collection of various deep learning architectures, models, and tips
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Official inference library for Mistral models
FaceChain is a deep-learning toolchain for generating your Digital-Twin.
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
Collection of useful data science topics along with articles, videos, and code
Structured state space sequence models
Algorithms for outlier, adversarial and drift detection
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
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.
PyMC educational resources
A replica of the AlphaZero methodology for deep reinforcement learning in Python
Natural Gradient Boosting for Probabilistic Prediction
Implementation of all RL algorithms in a simpler way
Code, data, and instructions for mapping orbits of asteroids in the solar system
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019
The book every data scientist needs on their desk.
An ongoing list of pandas quirks
Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke
Materials for following along with Hands-On Data Analysis with Pandas – Second Edition