A 21-lesson Microsoft course teaching how to build generative AI applications, with code examples in Python and TypeScript.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
A free 9-week course teaching data engineering by building an end-to-end data pipeline using tools like Docker, Terraform, Kafka, Spark, and dbt.
Open-source AI-oriented quantitative investment platform covering data, strategy research, backtesting, simulated and live trading.
A study guide and interview-prep curriculum for AI/ML technical roles at big tech, covering coding, ML breadth, system design, and behavioral rounds.
Stock AI Trader: 1-stop platform for learning, sim & live trading. Covers: stock basics, strategies, LLMs, factor mining, ML/DL/RL, graph nets, HFT, C++ deploy & JoinQuant code. 股票AI操盘手:一站式学习、模拟、实盘平台。涵盖:股票基础、策略、大模型、因子挖掘、机器学习/深度学习/强化学习、图网络、高频交易、C++部署及聚宽代码。
Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning | 涵盖预训练数据、分词器、Transformer、MoE、分布式训练、缩放定律、推理与对齐,6 项渐进代码作业,掌握 LLM 全栈知识
This project presents a comparative machine learning framework for heart attack risk prediction using Python. It includes data preprocessing, feature engineering, SMOTE for class balancing, cross validation, and performance evaluation of multiple ML models.
LeetCode for PyTorch — 65 ML/AI interview problems from real interviews at Google, Meta, Anthropic. Jupyter notebooks, an auto-grader, and an MCP AI tutor.
Sample notebooks, code, and apps demonstrating how to build with generative AI models on Google Cloud.
中文翻译的 Hands-On-Large-Language-Models (hands-on-llms),动手学习大模型
从 NLP 到 LLM 的算法全栈教程,在线阅读地址:https://datawhalechina.github.io/base-llm/
A collection of pre-trained, state-of-the-art models in the ONNX format
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
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 🚀.
A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.
A group of notebooks and other files which can help you learn AI from scratch.
Aircraft design optimization made fast through computational graph transformations (e.g., automatic differentiation). Composable analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.
Time-Series-Optimized Transformer for Observability
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Making Protein folding accessible to all!
Efficient few-shot learning with Sentence Transformers
Practical course about Large Language Models.
[CVPR 2025 Highlight] Official code and models for Encoder-only Mask Transformer (EoMT).
Knowledge-graph RAG built from structured metadata instead of LLM extraction. 929M edges, zero LLM calls, 83.2% on held-out PubMedQA. Case study: the full PubMed 2026 baseline.
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Code samples used on cloud.google.com
This is a Phi Family of SLMs book for getting started with Phi Models. Phi a family of open sourced AI models developed by Microsoft. Phi models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks
A high performance implementation of HDBSCAN clustering.
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.
Python tutorials in both Jupyter Notebook and youtube format.
GenMedia Creative Studio is a generative media user experience highlighting the use of Gemini, Gemini Omni, Veo, Gemini Image 🍌, Gemini TTS, Chirp 3, Lyria and other generative media APIs on Google Cloud.
Protein Graph Library
This repo is the homebase of a community driven course on Computer Vision with Neural Networks. Feel free to join us on the Hugging Face discord: hf.co/join/discord
SwiftUI, Jetpack Compose, Compose for Desktop and Compose for Web based Kotlin Multiplatform project (using CityBikes API http://api.citybik.es/v2/). Uses Room for local persistence
Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.
Google Cloud Platform Vertex AI end-to-end workflows for machine learning operations
🤗 Optimum Intel: Accelerate inference with Intel optimization tools
A prompting enhancement library for transformers-type text embedding systems
Fantasy Premier League Kotlin/Compose Multiplatform sample
A Python framework for performing information retrieval experiments, building on http://terrier.org/
Ноутбук для Гугл коллаба, в котором вы сможете к абсолютно любому медиа добавить субтитры и автоматически их первести на любой язык
PolluSense is an AI-driven pollution monitoring and forecasting system designed to identify pollution sources and predict Air Quality Index (AQI) levels using machine learning and deep learning techniques. The platform integrates real-time air quality data.
Hunyuan-DiT : A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
快速上手AI理论及应用实战:基础知识、Transformer、NLP、ML、DL、竞赛。含大量注释及数据集,力求每一位能看懂并复现。
Notebooks, code samples and reference for machine learning and generative ai on Google Cloud for the Advanced Solutions Lab (ASL) bootcamps.
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
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A video course with Jupyter notebooks that builds neural networks and backpropagation from scratch, from basics to Transformer language models.
Interactive Jupyter-based practice platform with 41 PyTorch problems, such as implementing softmax, attention, and GPT-2 from scratch, with automated grading.
[DEIMv2] Real Time Object Detection Meets DINOv3