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Awesome colab notebooks collection for ML experiments
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Courses
COURSES
| name | description | authors | links | colaboratory | update |
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| Python for Algorithmic Trading Cookbook | From raw market data to live algorithmic trading through 68 hands-on recipes across 15 chapters | Packt | 23.05.2026 | ||
| Time Series with PyTorch | Starting with PyTorch fundamentals, you will build neural networks from scratch and progress through recurrent networks, attention mechanisms, and transformers before exploring forecasting architectures such as N-BEATS, N-HiTS, and the Temporal Fusion Transformer | Packt | 08.05.2026 | ||
| GPU Computing with Python 3 and CUDA | How to accelerate Python applications using NVIDIA’s CUDA platform and a modern ecosystem of Python tools and libraries | Packt | 11.04.2026 | ||
| The Autodiff Cookbook | You'll go through a whole bunch of neat autodiff ideas that you can cherry pick for your own work, starting with the basics | Alex Wiltschko Matthew Johnson | 01.04.2026 | ||
| Practical RL | An open course on reinforcement learning in the wild | Pavel Shvechikov Nikita Putintsev Alexander Fritsler Oleg Vasilev |
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Dmitry Nikulin Mikhail Konobeev Ivan Kharitonov Ravil Khisamov Anna Klepova Fedor Ratnikov
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| 05.03.2026 |
| Deep Learning School course (ML + CV) | | Nina Konovalova |
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| 04.03.2026 |
| mlcourse.ai | Open Machine Learning Course | Yury Kashnitsky |
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| 24.01.2026 |
| Udacity Deep Learning class with TensorFlow | Learn how to apply deep learning to solve complex problems | Mark Daoust |
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| 14.01.2026 |
| Курс "Машинное обучение" на ФКН ВШЭ | Конспекты лекций, материалы семинаров и домашние задания (теоретические, практические, соревнования) по курсу "Машинное обучение", проводимому на бакалаврской программе "Прикладная математика и информатика" Факультета компьютерных наук Высшей школы экономики | Evgeny Sokolov |
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| 14.09.2025 |
| XAI | Дearning explainable artificial intelligence methods | Сабрина Садиех |
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| 05.09.2025 |
| LLM Engineering Essentials course | 12-week course, created by experts from academia and industry, is designed specifically for developers and engineers | Stanislav Fedotov Alexey Bukhtiyarov Nikita Pavlichenko Sergei Petrov
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Sergei Skvortsov Alex Umnov
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| 22.05.2025 |
| Understanding Language Models | Course deals with language models, in particular (but not exclusively so) on transformer-based language models like GPT-x or LLama | Michael Franke Carsten Eickhoff Polina Tsvilodub |
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| 17.04.2025 |
| Introduction to Deep Learning course | | Tatiana Gaintseva |
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| 24.01.2025 |
| ARENA | Provide talented individuals with the skills, tools, and environment necessary for upskilling in ML engineering, for the purpose of contributing directly to AI alignment in technical roles | Callum McDougall |
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| 30.12.2024 |
| Deep Learning Course at the University of Amsterdam | Series of Jupyter notebooks that are designed to help you understanding the "theory" from the lectures by seeing corresponding implementations | Pascal Mettes Melika Davood Zadeh Mohammadreza Salehidehnavi Danilo de Goede Phillip Lippe |
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| 17.10.2024 |
| Machine Learning Simplified | A Gentle Introduction to Supervised Learning | Andrew Wolf |
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| 29.08.2024 |
| Anthropic courses | Anthropic's educational courses | Anthropic |
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| 22.08.2024 |
| Deep RL Course | The Hugging Face Deep Reinforcement Learning Course | Thomas Simonini Omar Sanseviero Sayak Paul |
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| 24.06.2024 |
| Anthropic's Prompt Engineering Interactive Tutorial | Course is intended to provide you with a comprehensive step-by-step understanding of how to engineer optimal prompts within Claude | Anthropic |
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| 02.04.2024 |
| Generative AI for Beginners - A Course | A 12 Lesson course teaching everything you need to know to start building Generative AI applications | microsoft |
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| 22.02.2024 |
| Deep Reinforcement Learning | CS 285 at UC Berkeley | Sergey Levine Kyle Stachowicz Vivek Myers Joey Hong
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Kevin Black Michael Janner Vitchyr Pong Aviral Kumar
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| 29.08.2023 |
| npNLG | The course introduces the basics of NLG, neural language models and their implementation in PyTorch, as well as a selection of recent pragmatic neural NLG approaches | Michael Franke |
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| 09.11.2022 |
| DSP theory | Theory of digital signal processing: signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc | Alexander Kapitanov Vladimir Fadeev Karina Kvanchiani Elizaveta Petrova Andrei Makhliarchuk |
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| 18.10.2022 |
| Machine learning course | This course is broad and shallow, but author will provide additional links so that you can deepen your understanding of the ML method you need | Тимчишин Віталій |
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| 02.09.2021 |
| Intro to TensorFlow for Deep Learning | Dive into deep learning with this practical course on TensorFlow and the Keras API | Magnus Hyttsten Juan Delgado Paige Bailey |
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| 09.09.2020 |
| Introduction to TensorFlow Lite | Learn how to deploy deep learning models on mobile and embedded devices with TensorFlow Lite | Daniel Situnayake Paige Bailey Juan Delgado |
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| 09.09.2020 |
| NYU-DLSP20 | This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition | Yann LeCun Alfredo Canziani |
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| 30.10.2019 |
Projects
PROJECTS
| name | description | authors | links | colaboratory | update |
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| Kornia | Library is composed by a subset of packages containing operators that can be inserted within neural networks to train models to perform image transformations, epipolar geometry, depth estimation, and low-level image processing such as filtering and edge detection that operate directly on tensors | Edgar Riba Dmytro Mishkin Daniel Ponsa Ethan Rublee Gary Bradski | 05.08.2026 | ||
| Retrieval based Voice Conversion WebUI | An easy-to-use Voice Conversion framework based on VITS | 源文雨 | 04.08.2026 | ||
| SGLang | System comprising a frontend language and runtime for efficiently programming and executing complex structured language model programs with optimizations for cache reuse and structured output decoding. | Lianmin Zheng Liangsheng Yin Zhiqiang Xie Chuyue Sun |
others
Jeff Huang Cody Hao Yu Shiyi Cao Christos Kozyrakis Ion Stoica Joseph E. Gonzalez Clark Barrett Ying Sheng
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| 04.08.2026 |
| SHAP | SHapley Additive exPlanations is a game theoretic approach to explain the output of any machine learning model | Scott Lundberg Su-In Lee |
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| 03.08.2026 |
| YOLOv8 | State-of-the-art model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility | Glenn Jocher |
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| 01.08.2026 |
| YOLOv3 | You Only Look Once | Glenn Jocher |
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| 29.07.2026 |
| YOLOv5 | You Only Look Once | Glenn Jocher |
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| 29.07.2026 |
| dm_control | DeepMind Infrastructure for Physics-Based Simulation | Saran Tunyasuvunakool Alistair Muldal Yotam Doron Siqi Liu
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Steven Bohez Josh Merel Tom Erez Timothy Lillicrap Nicolas Heess Yuval Tassa
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| 28.07.2026 |
| ADK | Collection provides ready-to-use agents built on top of the Agent Development Kit, designed to accelerate your development process | Equious Ankur Sharma |
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| 24.07.2026 |
| OmegaConf | Hierarchical configuration system, with support for merging configurations from multiple sources providing a consistent API regardless of how the configuration was created | Omry Yadan |
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| 22.07.2026 |
| Agent Starter Pack | Collection of production-ready Generative AI Agent templates built for Google Cloud | Kristopher Overholt |
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| 21.07.2026 |
| AlphaFold | Highly accurate protein structure prediction | John Jumper Richard Evans Alexander Pritzel Tim Green
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Michael Figurnov Olaf Ronneberger Kathryn Tunyasuvunakool Russ Bates Augustin Žídek Anna Potapenko Alex Bridgland Clemens Meyer Simon Kohl Andrew Ballard Bernardino Romera-Paredes Stanislav Nikolov Rishub Jain
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| 14.07.2026 |
| GigaAM | SSL pretraining framework that leverages masked language modeling with targets derived from a speech recognition model | Aleksandr Kutsakov Alexandr Maximenko Georgii Gospodinov Pavel Bogomolov Fyodor Minkin |
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| 14.07.2026 |
| s | This paper introduces O-Voxel, a new sparse voxel representation and compression framework that enables high-fidelity, efficient 3D asset generation with flexible geometry and detailed appearance from learned compact latent spaces | Jianfeng Xiang Xiaoxue Chen Sicheng Xu Ruicheng Wang
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Zelong Lv Yu Deng Hongyuan Zhu Yue Dong Hao Zhao Nicholas Jing Yuan Jiaolong Yang
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| 09.07.2026 |
| NeMo | A conversational AI toolkit built for researchers working on automatic speech recognition, natural language processing, and text-to-speech synthesis | Oleksii Kuchaiev Jason Li Chip Huyen Oleksii Hrinchuk
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Ryan Leary Boris Ginsburg Samuel Kriman Stanislav Beliaev Vitaly Lavrukhin Jack Cook
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| 07.07.2026 |
| Anime Face Detector | Anime Face Detector using mmdet and mmpose | hysts |
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| 05.07.2026 |
| Chronos-2 | Pretrained, zero-shot time series forecasting model that uses group attention and synthetic multivariate training to perform univariate, multivariate, and covariate-informed forecasting with state-of-the-art accuracy across diverse real-world benchmarks. | Abdul Fatir Ansari Oleksandr Shchur Jaris Küken Andreas Auer
others
Boran Han Pedro Mercado Syama Sundar Rangapuram Huibin Shen Lorenzo Stella Xiyuan Zhang Mononito Goswami Shubham Kapoor Danielle C. Maddix Pablo Guerron Tony Hu Junming Yin Nick Erickson Prateek Mutalik Desai Hao Wang Huzefa Rangwala George Karypis Yuyang Wang Michael Bohlke-Schneider
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| 02.07.2026 |
| Nano Banana | An image generation and editing model powered by generative artificial intelligence and developed by Google DeepMind | Guillaume Vernade |
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| 30.06.2026 |
| Presidio | Context aware, pluggable and customizable PII de-identification service for text and images | Omri Mendels |
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| 28.06.2026 |
| Weaver | Lightweight autoregressive adapter for factorized draft models that constructs proposal trees from top-K marginals to restore conditional dependencies and enable faster speculative decoding with optimized tree verification and CUDA kernels in SGLang. | Yuma Oda Ryan Mathieu Roman Knyazhitskiy Artur Chakhvadze |
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| 24.06.2026 |
| TransformerLens | Library for doing mechanistic interpretability of GPT-2 Style language models | Neel Nanda Joseph Bloom |
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| 22.06.2026 |
| Hyperopt | Python library for serial and parallel optimization over awkward search spaces, which may include real-valued, discrete, and conditional dimensions | James Bergstra Dan Yamins David Cox |
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| 21.06.2026 |
| highway-env | A collection of environments for autonomous driving and tactical decision-making tasks | Edouard Leurent |
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| 19.06.2026 |
| SentencePiece | An unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabulary size is predetermined prior to the neural model training | Taku Kudo John Richardson |
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| 14.06.2026 |
| RF-DETR | Lightweight, real-time detection transformer that uses weight-sharing neural architecture search to automatically discover optimal accuracy-latency tradeoffs for object detection across diverse target datasets. | Isaac Robinson Peter Robicheaux Matvei Popov Deva Ramanan Neehar Peri |
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| 13.06.2026 |
| Mem0 | Self-improving memory layer for LLM applications, enabling personalized AI experiences that save costs and delight users | Prateek Chhikara Dev Khant Saket Aryan Taranjeet Singh Deshraj Yadav |
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| 13.06.2026 |
| Swarm | Educational framework exploring ergonomic, lightweight multi-agent orchestration | Ilan Bigio James Hills Shyamal Anadkat Charu Jaiswal
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Colin Jarvis Katia Guzman
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| 07.06.2026 |
| Duo | This software project implements Duo, a diffusion-based language modeling framework that improves discrete diffusion text generation using Gaussian-guided curriculum learning and Discrete Consistency Distillation for faster training and few-step sampling. | Subham Sekhar Sahoo Justin Deschenaux Aaron Gokaslan Guanghan Wang
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Justin Chiu Volodymyr Kuleshov
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| 03.06.2026 |
| Magenta RT | An open-weights live music model that allows you to interactively create, control and perform music in the moment | Chris Donahue |
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| 02.06.2026 |
| TorchGeo | PyTorch domain library that provides datasets, transforms, samplers, and pre-trained models specific to geospatial data | Adam Stewart Caleb Robinson Isaac Corley Anthony Ortiz
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Juan Lavista Ferres Arindam Banerjee
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| 01.06.2026 |
| pymdp | Package for simulating Active Inference agents in Markov Decision Process environments | Conor Heins Alec Tschantz Beren Millidge Brennan Klein
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Arun Niranjan Daphne Demekas
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| 29.05.2026 |
| ActionMesh | Temporal 3D diffusion framework that generates production-ready, topology-consistent animated 3D meshes from inputs like video, text, or static 3D shapes in a fast, feed-forward manner. | Remy Sabathier David Novotny Niloy J. Mitra Tom Monnier |
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| 28.05.2026 |
| Lyria 2 | Delivers high-fidelity music and professional-grade audio, capturing subtle nuances across a range of genres and intricate compositions | Katie Nguyen |
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| 13.05.2026 |
| Video Seal | Comprehensive framework for neural video watermarking and a competitive open-sourced model | Pierre Fernandez Hady Elsahar Zeki Yalniz Alexandre Mourachko |
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| 11.05.2026 |
| Google Cloud Text-to-Speech | Enables easy integration of Google text recognition technologies into developer applications | Holt Skinner Ivan Nardini |
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| 07.05.2026 |
| Imagen 4 | Text-to-image model, with photorealistic images, near real-time speed, and sharper clarity | Katie Nguyen |
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| 06.05.2026 |
| CrewAI | Lean, lightning-fast Python framework built entirely from scratch—completely independent of LangChain or other agent frameworks | João Moura |
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| 20.04.2026 |
| CodeGemma | How to load, fine-tune and deploy CodeGemma model on SQL by utilising Hugging Face | Carlo Fisicaro |
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| 20.04.2026 |
| Hello, many worlds | This tutorial shows how a classical neural network can learn to correct qubit calibration errors | Michael Broughton |
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| 18.04.2026 |
| Text Generation Web UI | The best local UI for large language models, with easy setup and powerful features. 100% offline. | oobabooga |
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| 13.04.2026 |
| DataChain | AI-dataframe to enrich, transform and analyze data from cloud storages for ML training and LLM apps | Daniel K |
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| 13.04.2026 |
| JAX MD | Differentiable physics and molecular dynamics simulation framework in JAX that enables scalable, GPU-accelerated simulations and end-to-end optimization of entire trajectories, with flexible primitives and neural network integration. | Samuel S. Schoenholz Ekin D. Cubuk |
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| 05.04.2026 |
| GraphCast | Learning skillful medium-range global weather forecasting | Rémi Lam Alvaro Sanchez-Gonzalez Matthew Willson Peter Wirnsberger
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Meire Fortunato Ferran Alet Suman Ravuri Timo Ewalds Zach Eaton-Rosen Weihua Hu Alexander Merose Stephan Hoyer George Holland Oriol Vinyals Jacklynn Stott Alexander Pritzel Shakir Mohamed Peter Battaglia
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