This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
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
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
:satellite: Simple and ready-to-use tutorials for TensorFlow
- tensorflow
- python
- deep-learning
- deep-learning-tutorial
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
- pytorch
- pytorch-tutorials
- pytorch-tutorials-cn
- deep-learning
Toturials coming with the "data science roadmap" picture.
From the basics to slightly more interesting applications of Tensorflow
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
Quantitative analysis, strategies and backtests
- quantitative-finance
- quantitative-trading
- portfolio-management
- risk-management
Instructional notebooks on music information retrieval.
- ipython-notebook
- music-information-retrieval
- python
- machine-learning
CatBoost tutorials repository
- catboost
- tutorials
- ipython-notebook
- ipython
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
- seq2seq
- tensorflow
- tensorflow-tutorials
- python
tutorials made for biologists to learn deep learning
- biologists
- keras
- deeplearning
- deep-learning
Big Data essentials: Hadoop, MapReduce, Spark. Explore tutorials and demos in Jupyter notebooks—most are self-contained and live, ready to run with a click.