This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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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 collection of various deep learning architectures, models, and tips
Pytorch🍊🍉 is delicious, just eat it! 😋😋
TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
- time-series
- time-series-forecasting
- deep-learning
- forecasting
felixge's notes on the various go profiling methods that are available.
- pprof
- profiling
- go
- golang
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
A collection of IPython notebooks covering various topics.
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
- ai
- chromadb
- cookbooks
- faiss
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
Doing simple retrieval from LLM models at various context lengths to measure accuracy
Various Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau
- stock-market
- stock-analysis
- trading-strategies
- technical-analysis
This repository showcases a selection of machine learning projects undertaken to understand and master various ML concepts. Each project reflects commitment to applying theoretical knowledge to practical scenarios, demonstrating proficiency in machine learning techniques and tools.
- machine-learning-projects
- projects
- ml-project
- python-project
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.
- deep-learning
- artificial-neural-networks
- continual-learning
- lifelong-learning
Notebooks covering mathematical analysis of ZKP building blocks, algorithm implementations of various proof systems, and protocol optimization techniques.
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
- convolutional-networks
- deep-learning
- yolo2
- realtime
Various ipython notebooks
- perceptron
- bitcoin
- blockchain
- python
An easy/swift-to-adapt PyTorch-Lighting template. 套壳模板，简单易用，稍改原来Pytorch代码，即可适配Lightning。You can translate your previous Pytorch code much easier using this template, and keep your freedom to edit all the functions as well. Big-project-friendly as well. No need to rewrite your config in hydra.
- pytorch
- pytorch-lightning
- pytorch-lightning-template
- best-practices
The codes I made while I practiced various TensorFlow examples
Implementation of various topic models
Various Jupyter notebooks about Common Crawl data
- jupyter-notebook
- common-crawl
- aws-athena
- webarchiving
Various examples of notebooks for working with web archives with the Archives Unleashed Toolkit, and derivatives generated by the Archives Unleashed Toolkit.
- notebooks
- pyspark-notebook
- juypter-notebook
- spark
Slides and materials for various talks I've given