21 Lessons, Get Started Building with Generative AI
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Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
18 Lessons to Get Started Building AI Agents
- agentic-ai
- agentic-framework
- agentic-rag
- ai-agents
12 Weeks, 24 Lessons, AI for All!
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
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, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org
- hacking
- penetration-testing
- hacking-series
- cybersecurity
Python programs, usually short, of considerable difficulty, to perfect particular skills.
- python
- python-3
- programming
- practice
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
- machine-learning
- trading
- investment
- finance
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
Get started with building Fullstack Agents using Gemini 2.5 and LangGraph
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
- computer-vision
- deep-learning
- drug-discovery
- forecasting
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
- deep-learning
- mit
- self-driving-cars
- deep-reinforcement-learning
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
- machine-learning
- deep-learning
- lstm
- human-activity-recognition
Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano
TranslatedLearning machine learning and quantitative analysis, in progress
ChatGPT Python Applications integrated with third party libraries and modules
How to create a Cartoonizer Android app with TensorFlow Lite models.
- tensorflow-lite
- tflite
- computer-vision
- gans
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.