{"id":16188,"url":"https://github.com/firmai/awesome-google-colab","name":"awesome-google-colab","description":"Google Colaboratory Notebooks and Repositories (by @firmai)","projects_count":73,"last_synced_at":"2026-09-01T12:00:33.383Z","repository":{"id":37693220,"uuid":"221091581","full_name":"firmai/awesome-google-colab","owner":"firmai","description":"Google Colaboratory Notebooks and Repositories (by @firmai)","archived":false,"fork":false,"pushed_at":"2022-03-10T12:44:32.000Z","size":1666,"stargazers_count":1510,"open_issues_count":2,"forks_count":262,"subscribers_count":56,"default_branch":"master","last_synced_at":"2026-08-22T21:50:27.315Z","etag":null,"topics":["coursera","data-science","google-colab","google-colab-notebook","jupyter-notebook","machine-learning","notebooks","python","tutorial"],"latest_commit_sha":null,"homepage":"https://google-colab.com/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/firmai.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-11-11T23:53:59.000Z","updated_at":"2026-08-21T04:39:37.000Z","dependencies_parsed_at":"2022-07-18T10:38:57.595Z","dependency_job_id":null,"html_url":"https://github.com/firmai/awesome-google-colab","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/firmai/awesome-google-colab","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/firmai%2Fawesome-google-colab","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/firmai%2Fawesome-google-colab/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/firmai%2Fawesome-google-colab/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/firmai%2Fawesome-google-colab/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/firmai","download_url":"https://codeload.github.com/firmai/awesome-google-colab/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/firmai%2Fawesome-google-colab/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":37018574,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-08-22T15:14:58.755Z","status":"online","status_checked_at":"2026-09-01T02:00:05.433Z","response_time":53,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-13T12:53:56.189Z","updated_at":"2026-09-01T12:00:33.384Z","primary_language":"Jupyter Notebook","list_of_lists":false,"displayable":true,"categories":["Ten Favourite Colab Notebooks","Applications","Technologies","Course and Tutorial"],"sub_categories":[],"readme":"# Unofficial Google Colaboratory Notebook and Repository Gallery\n\n**Please contact me to take over and revamp this repo (it gets around 30k views and 200k clicks per year), I don't have time to update or maintain it - message 15/03/2021**\n\nA curated list of repositories with fully functional click-and-run colab notebooks with data, code and description. The code in these repositories are in Python unless otherwise stated. \n\nTo learn more about they whys and hows of Colab [see this post](https://medium.com/@firmai/google-colab-for-reproducible-research-webapps-and-data-science-fb1beec30304). For a few tips and tricks see [this post](https://www.google-colab.com/google-colab-tips-and-tricks/). \n\n**If you have just a single notebook to submit, use the website https://google-colab.com/, it is really easy, on the top right corner click 'submit +'. The earlier you post the more visibility you will get over time**\n\n***Caution:*** This is a work in progress, please contribute by adding colab functionality to your own data science projects on github or requestion it from the authors.\n\n---\n \nIf you want to contribute to this list (please do), send me a pull request or contact me [@dereknow](https://twitter.com/dereknow) or on [linkedin](https://www.linkedin.com/in/snowderek/).\nAlso, a listed repository should be fixed or removed:\n\n* if there are no data or descriptive text in the notebooks.\n* the code throws out errors.\n---\n* **LinkedIn**: https://www.linkedin.com/company/google-colab-notebooks/\n* **Twitter**: https://twitter.com/ColabNotebooks\n* **Facebook**: https://www.facebook.com/ColabNotebooks/\n* **Reddit**: https://www.reddit.com/r/GoogleColabNotebooks/\n\n---\nApart from the colab-enabled repositories listed below, you can also with a bit of work run github jupyter notebooks directly on Google Colaboratory using CPU/GPU/TPU runtimes by replacing https://github.com in the URL by https://colab.research.google.com/github/. No local installation of Python is required. Of course, these notebooks would have to be adapted to ingest the necessary data and modules.\n\n#### Search for 'Colab' or the 'Open in Colab' Badge to Open the Colabotary Notebooks in Each Repository\n\n## Ten Favourite Colab Notebooks\n\n#### For more see https://google-colab.com/\n\n* [Advanced Business Analytics and Mathematics in Python](https://github.com/firmai/business-analytics-and-mathematics-python)\n* [Traffic Counting with OpenCV](https://colab.research.google.com/drive/12N4m_RYKqrpozRzh9qe7nQE_sIqQH9U8)\n* [A collection of 25+ Reinforcement Learning Trading Strategies](https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW)\n* [Numerical Solutions for PDEs](https://colab.research.google.com/drive/1lIJ6guEAH5NQObefYBJ7S_Jm21IlJSOo)\n* [Bankruptcy Prediction with Python](https://colab.research.google.com/drive/1ozRafLRWiVL9bwF5ihRUa4gz4rURKEW6)\n* [Facebook Detectron2](https://colab.research.google.com/drive/16jcaJoc6bCFAQ96jDe2HwtXj7BMD_-m5)\n* [Data Sciencing with Twitter](https://colab.research.google.com/drive/1WIcVZgbrU0DYOQqaxuaCLKY6CoLBV18O)\n* [Medical Questions and Answers](https://colab.research.google.com/drive/11hAr1qo7VCSmIjWREFwyTFblU2LVeh1R)\n* [BERT Movie Reviews](https://colab.research.google.com/github/google-research/bert/blob/master/predicting_movie_reviews_with_bert_on_tf_hub.ipynb)\n* [Recurrent Neural Networks for Predictive Maintenance](https://colab.research.google.com/drive/1tjIOud2Cc6smmvZsbl-QDBA6TLA2iEtd)\n* [AirBnB Sydney Rent Evaluation](https://colab.research.google.com/drive/16ILDbLl6rCD0S3r8LrEV7WXpC8LpDuo7)\n\n\n\n# Repository Table of Contents\n\u003c!-- MarkdownTOC depth=4 --\u003e\n\n- [Courses and Tutorials](#course)\n- [Technologies](#tech)\n    - [Text](#tech-text)\n    - [Image](#tech-image)\n    - [Voice](#tech-voice)\n    - [Reinforcement Learning](#tech-voice)\n    - [Visualisation](#tech-viz)\n    - [Operational](#tech-op)\n    - [Other](#tech-other)\n- [Applications](#app)\n    - [Finance](#app-fin)\n    - [Artistic](#app-art)\n    - [Medical](#app-med)\n    - [Operations](#app-op)\n\n    \n\n\u003ca name=\"course\"\u003e\u003c/a\u003e\n## Course and Tutorial\n\n* [Python Data Science Notebook](https://github.com/jakevdp/PythonDataScienceHandbook) - Python Data Science Handbook: full text in Jupyter Notebooks \n\n* [ML and EDA](https://github.com/noahgift/functional_intro_to_python#safari-online-training--essential-machine-learning-and-exploratory-data-analysis-with-python-and-jupyter-notebook) - Functional, data science centric introduction to Python.\n\n* [Python Business Analytics](https://github.com/firmai/python-business-analytics) - Python solutions to solve practical business problems. \n\n* [Deep Learning Examples](https://github.com/tugstugi/dl-colab-notebooks) - Try out deep learning models online on Google Colab \n\n* [Hvass-Labs](https://github.com/Hvass-Labs/TensorFlow-Tutorials) - TensorFlow Tutorials with YouTube Videos \n\n* [MIT deep learning](https://github.com/lexfridman/mit-deep-learning) - Tutorials, assignments, and competitions for MIT Deep Learning related courses.\n\n* [NLP Tutorial]( https://github.com/graykode/nlp-tutorial) - Natural Language Processing Tutorial for Deep Learning Researchers \n\n* [DeepSchool.io](https://github.com/sachinruk/deepschool.io) - Deep Learning tutorials in jupyter notebooks. \n\n* [Deep NLP Course](https://github.com/DanAnastasyev/DeepNLP-Course) - A deep NLP Course \n\n* [pyprobml](https://github.com/probml/pyprobml) - Python code for \"Machine learning: a probabilistic perspective\" \n\n* [MIT 6.S191](https://github.com/aamini/introtodeeplearning_labs) - Lab Materials for MIT 6.S191: Introduction to Deep Learning\n\n* [HSE NLP](https://github.com/hse-aml/natural-language-processing) - Resources for \"Natural Language Processing\" Coursera course\n\n* [Real Word NLP](https://github.com/mhagiwara/realworldnlp) - Example code for \"Real-World Natural Language Processing\"\n\n* [Notebooks](https://github.com/zaidalyafeai/Notebooks) - Machine learning notebooks in different subjects optimized to run in google collaboratory \n\n\n\n\n    \n## Technologies\n\u003ca name=\"tech\"\u003e\u003c/a\u003e\n\n\u003ca name=\"tech-text\"\u003e\u003c/a\u003e\n#### Text\n\n* [BERT](https://github.com/google-research/bert) - TensorFlow code and pre-trained models for BERT \n\n* [XLNet](https://github.com/zihangdai/xlnet) - XLNet: Generalized Autoregressive Pretraining for Language Understanding\n\n* [DeepPavlov Tutorials](https://github.com/deepmipt/dp_tutorials) - An open source library for deep learning end-to-end dialog systems and chatbots.\n\n* [TF NLP](https://github.com/zhedongzheng/tensorflow-nlp) - Projects, Practice, NLP, TensorFlow 2, Google Colab \n\n* [SparkNLP](https://github.com/JohnSnowLabs/spark-nlp) - State of the Art Natural Language Processing \n\n* [Deep Text Recognition](https://github.com/clovaai/deep-text-recognition-benchmark) - Text recognition (optical character recognition) with deep learning methods.\n\n* [BERTScore](https://github.com/Tiiiger/bert_score) - Automatic Evaluation Metric for Bert.\n\n* [Text Summurisation](https://github.com/theamrzaki/text_summurization_abstractive_methods) - Multiple implementations for abstractive text summurization\n\n* [GPT-2 Colab](https://github.com/ak9250/gpt-2-colab) - Retrain gpt-2 in colab \n \n\n\u003ca name=\"tech-image\"\u003e\u003c/a\u003e\n#### Image\n\n* [DeepFaceLab](https://github.com/chervonij/DFL-Colab) - DeepFaceLab is a tool that utilizes machine learning to replace faces in videos.\n\n* [CycleGAN and PIX2PIX](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix) - Image-to-Image Translation in PyTorch \n\n\n* [DeOldify](https://github.com/jantic/DeOldify) - A Deep Learning based project for colorizing and restoring old images (and video!) \n\n* [Detectron2](https://github.com/facebookresearch/detectron2) - Detectron2 is FAIR's next-generation research platform for object detection and segmentation.\n\n* [EfficientNet - PyTorch]( https://github.com/lukemelas/EfficientNet-PyTorch) - A PyTorch implementation of EfficientNet \n\n\n* [Faceswap GAN](https://github.com/shaoanlu/faceswap-GAN) - A denoising autoencoder + adversarial losses and attention mechanisms for face swapping. \n\n* [Neural Style Transfer](https://github.com/titu1994/Neural-Style-Transfer) - Keras Implementation of Neural Style Transfer from the paper \"A Neural Algorithm of Artistic Style\"\n\n* [Compare GAN](https://github.com/google/compare_gan) - Compare GAN code\n\n* [hmr](https://github.com/akanazawa/hmr) - Project page for End-to-end Recovery of Human Shape and Pose \n\n\n\u003ca name=\"tech-voice\"\u003e\u003c/a\u003e\n#### Voice\n\n* [Spleeter]( https://github.com/deezer/spleeter) - Deezer source separation library including pretrained models.\n\n* [TTS](https://github.com/mozilla/TTS) - Deep learning for Text to Speech \n\n\u003ca name=\"tech-rl\"\u003e\u003c/a\u003e\n#### Reinforcement Learning\n\n* [Dopamine](https://github.com/google/dopamine) - Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. \n\n\n* [Sonnet](https://github.com/deepmind/sonnet) - TensorFlow-based neural network library\n\n\n* [OpenSpiel](https://github.com/deepmind/open_spiel) - Collection of environments and algorithms for research in general reinforcement learning and search/planning in games. \n\n* [TF Agents](https://github.com/tensorflow/agents) - TF-Agents is a library for Reinforcement Learning in TensorFlow \n\n* [bsuite](https://github.com/deepmind/bsuite) - Collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent\n\n* [TF Generative Models](https://github.com/timsainb/tensorflow2-generative-models) - mplementations of a number of generative models in Tensorflow\n\n \n* [DQN to Rainbow]( https://github.com/Curt-Park/rainbow-is-all-you-need) - A step-by-step tutorial from DQN to Rainbow \n\n\n\u003ca name=\"tech-viz\"\u003e\u003c/a\u003e\n#### Visualisation\n\n* [Altair]( https://github.com/altair-viz/altair) - Declarative statistical visualization library for Python\n\n* [Altair Curriculum](https://github.com/uwdata/visualization-curriculum) - A data visualization curriculum of interactive notebooks.\n\n* [bertviz](https://github.com/jessevig/bertviz) - Tool for visualizing attention in the Transformer model \n\n* [TF Graphics](https://github.com/tensorflow/graphics) - TensorFlow Graphics: Differentiable Graphics Layers for TensorFlow \n\n* [deepreplay](https://github.com/dvgodoy/deepreplay) - Generate visualizations as in my \"Hyper-parameters in Action!\"\n\n\u003ca name=\"tech-op\"\u003e\u003c/a\u003e\n#### Operational\n\n* [PySyft](https://github.com/OpenMined/PySyft) - A library for encrypted, privacy preserving machine learning \n\n* [Mindsdb](https://github.com/mindsdb/mindsdb) - Framework to streamline use of neural networks\n\n* [Ranking](https://github.com/tensorflow/ranking) - Learning to Rank in TensorFlow \n\n* [TensorNetwork](https://github.com/google/TensorNetwork) - A library for easy and efficient manipulation of tensor networks. \n\n* [JAX](https://github.com/google/jax) - Composable transformations of Python+NumPy programs\n\n \n* [BentoML]( https://github.com/bentoml/BentoML) - A platform for serving and deploying machine learning models\n\n\u003ca name=\"tech-other\"\u003e\u003c/a\u003e\n#### Other\n\n* [Transfer learning NLP](https://github.com/huggingface/naacl_transfer_learning_tutorial) - code for the tutorial on Transfer Learning in NLP held at NAACL 2019\n\n* [BDL Benchmarks](https://github.com/OATML/bdl-benchmarks) - Bayesian Deep Learning Benchmarks \n\n\n\u003ca name=\"app\"\u003e\u003c/a\u003e\n## Applications\n\n\n\u003ca name=\"app-fin\"\u003e\u003c/a\u003e\n#### Finance\n\n* [RLTrader](https://github.com/notadamking/RLTrader) - A cryptocurrency trading environment using deep reinforcement learning and OpenAI's gym\n\n* [TF Quant Finance](https://github.com/google/tf-quant-finance) - High-performance TensorFlow library for quantitative finance. \n\n* [TensorTrade](https://github.com/notadamking/tensortrade) - An open source reinforcement learning framework for robust trading agents\n\n\n\u003ca name=\"app-art\"\u003e\u003c/a\u003e\n#### Artistic\n\n* [Rapping NN](https://github.com/robbiebarrat/rapping-neural-network) - Rap song writing recurrent neural network trained on Kanye West's entire discography \n\n* [Photogrammetry](https://github.com/alicevision/meshroom/wiki/Meshroom-in-Google-Colab-(cloud)) - Render Photogrammetry With Colab's Cloud GPU's With Meshroom. \n\n* [dl4g](https://github.com/smartgeometry-ucl/dl4g) - Deep Learning for Graphics \n\n\u003ca name=\"app-med\"\u003e\u003c/a\u003e\n#### Medical\n\n* [DocProduct]( https://github.com/re-search/DocProduct) - Medical Q\u0026A with Deep Language Models \n\n\u003ca name=\"app-op\"\u003e\u003c/a\u003e\n#### Operations\n\n* [LSTM Predictive Maintenance](https://github.com/umbertogriffo/Predictive-Maintenance-using-LSTM) - Example of Multiple Multivariate Time Series Prediction with LSTM\n\n\n\n\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/firmai%2Fawesome-google-colab/projects"}