《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM …

A comprehensive guide to building RAG-based LLM applications for production.

This is a computer vision project that utilizes object detection algorithms to analyze football matches videos by finding the position of players, ball and referees on the football pitch and findin…

Jupyter notebooks used in the course Numerical Analysis (MAST 334 and MATH 354) at Concordia University