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Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
The TypeScript AI agent framework. ⚡ Assistants, RAG, observability. Supports any LLM: GPT-4, Claude, Gemini, Llama.
Finetune Qwen3, Llama 4, TTS, DeepSeek-R1 & Gemma 3 LLMs 2x faster with 70% less memory! 🦥
TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and support state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorR…
AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation
Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 3, Mistral Small 3.1 and other large language models.
A simpler site generator. Transforms a directory of templates (of varying types) into HTML.
The official Go client library for the Polygon REST and WebSocket API.
The official Python client library for the Polygon REST and WebSocket API.
The Forge Cross-Platform Framework PC Windows, Steamdeck (native), Ray Tracing, macOS / iOS, Android, XBOX, PS4, PS5, Switch, Quest 2
Minimal examples of data structures and algorithms in Python
Chronos: Pretrained Models for Probabilistic Time Series Forecasting
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
Code for Machine Learning for Algorithmic Trading, 2nd edition.
All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.
Jupyter Notebooks and code for the book Python for Algorithmic Trading (O'Reilly) by Yves Hilpisch.
Adds email sending capability to a Nuxt.js app. Adds a server route, an injected variable, and uses nodemailer to send emails.
Supplemental Material for Algorithmic Trading and Quantitative Strategies
Python Backtesting library for trading strategies
Understanding Deep Learning - Simon J.D. Prince
A simple Python wrapper around inotify. No fancy bells and whistles, just a literal wrapper with ctypes.
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 mode…
Boost LaTeX typesetting efficiency with preview, compile, autocomplete, colorize, and more.
The code used for the article "Interactive Brokers Python API (Native) – A Step-by-step Guide" on the AlgoTrading101 Blog