12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

A latent text-to-image diffusion model

Examples and guides for using the OpenAI API

Google Research

Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Course Files for Complete Python 3 Bootcamp Course on Udemy

This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security,…

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

Instruct-tune LLaMA on consumer hardware

This repository contains the source code for the paper First Order Motion Model for Image Animation

A multi-voice TTS system trained with an emphasis on quality

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

High-Resolution Image Synthesis with Latent Diffusion Models

Kubernetes community content

LAVIS - A One-stop Library for Language-Vision Intelligence

Lists of company wise questions available on leetcode premium. Every csv file in the companies directory corresponds to a list of questions on leetcode for a specific company based on the leetcode …

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Code release for NeRF (Neural Radiance Fields)

Automatic extraction of relevant features from time series:

A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like YOLO11, RT-DETR, SAM …

Labs and demos for courses for GCP Training (http://cloud.google.com/training).

Lab Materials for MIT 6.S191: Introduction to Deep Learning

Using Low-rank adaptation to quickly fine-tune diffusion models.

Overview and tutorial of the LangChain Library

Taming Transformers for High-Resolution Image Synthesis

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Reference models and tools for Cloud TPUs.

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.