Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Examples and guides for using the OpenAI API

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.

Overview and tutorial of the LangChain Library

Collection of notebooks about quantitative finance, with interactive python code.

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…

Everything you need to know to build your own RAG application

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

Efficient few-shot learning with Sentence Transformers

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning

This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.

Benchmark LLMs by fighting in Street Fighter 3! The new way to evaluate the quality of an LLM

Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry thr…

Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SP…

Quantitative Interview Preparation Guide, updated version here ==>

All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.

Sources codes for: Mastering Python for Finance, Second Edition

Technical and sentiment analysis to predict the stock market with machine learning models based on historical time series data and news article sentiment collected using APIs and web scraping.

Python codes for Introduction to Computational Stochastic PDE

predicting US Federal interest rate changes using the text of Fed press releases

In this project we will be using the publicly available and Kaggle-popular LendingClub data set to train Linear Regression and Extreme Gradient Descent Boosted Decision Tree models to predict inte…

KOSA GPT_Ochestration