{"id":39015,"url":"https://github.com/ramene/awesome-deepnote","name":"awesome-deepnote","description":"A curated list of extensions, python packages, machine learning and collaborative notebooks ready to run in Deepnote.","projects_count":41,"last_synced_at":"2026-07-11T11:00:23.959Z","repository":{"id":65815965,"uuid":"302747117","full_name":"ramene/awesome-deepnote","owner":"ramene","description":"A curated list of extensions, python packages, machine learning and collaborative notebooks ready to run in Deepnote.","archived":false,"fork":false,"pushed_at":"2026-06-15T04:15:50.000Z","size":1273,"stargazers_count":59,"open_issues_count":0,"forks_count":5,"subscribers_count":6,"default_branch":"main","last_synced_at":"2026-06-23T08:04:11.608Z","etag":null,"topics":["awesome","awesome-list","collections","data-visualization","datascience","deep-learning","deep-neural-networks","deepnote","gans","hashicorp","hashicorp-waypoint","lists","notebooks","python","scikit-learn","visualizations"],"latest_commit_sha":null,"homepage":"https://ramene.github.io/awesome-deepnote/","language":null,"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/ramene.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":"2020-10-09T20:31:00.000Z","updated_at":"2026-06-17T23:36:34.000Z","dependencies_parsed_at":"2023-02-11T22:25:11.676Z","dependency_job_id":null,"html_url":"https://github.com/ramene/awesome-deepnote","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ramene/awesome-deepnote","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramene%2Fawesome-deepnote","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramene%2Fawesome-deepnote/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramene%2Fawesome-deepnote/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramene%2Fawesome-deepnote/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ramene","download_url":"https://codeload.github.com/ramene/awesome-deepnote/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramene%2Fawesome-deepnote/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35360371,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-11T02:00:05.354Z","response_time":104,"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":"2024-01-13T14:00:02.213Z","updated_at":"2026-07-11T11:00:23.959Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Other Awesome Lists","General","Resources","Integrations"],"sub_categories":["License"],"readme":"# Awesome Deepnote [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)  [\u003cimg height=\"21\" src=\"https://beta.deepnote.com/buttons/launch-in-deepnote.svg\"\u003e](https://github.com/SuNaden/deepnote-launch-example) \n\nA curated [awesome](https://github.com/topics/awesome) list of deepnote notebooks, extensions and resources. [Deepnote](http://deepnote.com) is a new kind of data science notebook. Jupyter-compatible with real-time collaboration and easy deployment.\n\n\u003cdiv align=\"right\" style=\"text-align:right\"\u003e\u003ci\u003e\u003ca href=\"https://github.com/topics/deepnote\"\u003e#deepnote\u003c/a\u003e, \u003ca href=\"https://github.com/topics/jupyter-kernels\"\u003e#jupyter-kernels\u003c/a\u003e, \u003ca href=\"https://github.com/topics/machine-learning\"\u003e#machine-learning\u003c/a\u003e\u003cbr\u003e\nsearch: \u003ca href=\"https://github.com/search?type=Repositories\u0026q=deepnote\"\u003e deepnote\u003c/a\u003e\u003c/i\u003e\u003c/div\u003e\n\n\u003cdiv align=\"center\"\u003e\n\u003cimg  width=\"160\"  src=\"https://deepnote.com/static/landing/logo.svg\"  alt=\"Jupyter logo\"\u003e\n\u003c/div\u003e\n\n## General\n\n#### _matplotlib, plotly_\n-  [Visual data exploration with Virginia's public COVID-19 cases dataset](https://github.com/jammy-bot/va-covid-eda) by [Jamal Dargan](https://github.com/jammy-bot)\n#### _anaconda, miniconda_\n-  [Using Conda in Deepnote in 3 simple steps](https://beta.deepnote.com/project/1e061457-9c0a-412a-a8fa-c08358928ba2)\n\n#### _scikit-learn, tensorflow, keras_\n- [ \u003csub\u003e\u003csub\u003e\u003cimg height=\"20\" src=\"https://deepnote.com/buttons/launch-in-deepnote.svg\"\u003e\u003c/sub\u003e\u003c/sub\u003e](https://deepnote.com/launch?template=deepnote\u0026url=https%3A%2F%2Fgithub.com%2Fmatthew-e-thomas%2Fdeeptnote-credit-card-fraud%2Fblob%2Fmaster%2Fcredit_card_fraud_ml.ipynb)  [Detect Credit Card Fraud](https://github.com/matthew-e-thomas/deeptnote-credit-card-fraud)  \n- [ \u003csub\u003e\u003csub\u003e\u003cimg height=\"20\" src=\"https://deepnote.com/buttons/launch-in-deepnote.svg\"\u003e\u003c/sub\u003e\u003c/sub\u003e](https://deepnote.com/launch?template=deepnote\u0026url=https%3A%2F%2Fgithub.com%2Falfarias%2Fcustomer-churn-prediction%2Fblob%2Fmaster%2Fnotebooks%2Fcustomer-churn-prediction.ipynb%29)  [Customer Churn Prediction](https://github.com/alfarias/customer-churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb) \n- [ \u003csub\u003e\u003csub\u003e\u003cimg height=\"20\" src=\"https://deepnote.com/buttons/launch-in-deepnote.svg\" alt=\"Peter Norvig\"\u003e\u003c/sub\u003e\u003c/sub\u003e](https://deepnote.com/launch?template=data-science\u0026url=https%3A//github.com/ageron/handson-ml/blob/master/02_end_to_end_machine_learning_project.ipynb)  [Hands-on Machine Learning with Scikit-Learn and TensorFlow](https://learning.oreilly.com/library/view/hands-on-machine-learning/9781491962282/)\n- [ \u003csub\u003e\u003csub\u003e\u003cimg alt=\"by Peter Norvig\" height=\"20\" src=\"https://deepnote.com/buttons/launch-in-deepnote.svg\"\u003e\u003c/sub\u003e\u003c/sub\u003e](https://deepnote.com/launch?template=data-science\u0026url=https%3A//github.com/ageron/handson-ml/blob/master/02_end_to_end_machine_learning_project.ipynb)   [Deep Learning with TensorFlow 2 and Keras](https://github.com/ageron/tf2_course)\n\n#### _tensorboard_\n-  [Tensorboard with ngrok](https://deepnote.com/project/d9ef0f3d-e2e3-40ef-8f40-2dc37fb22b88#%2Ftensorboard.ipynb) \n-  [Scraping the EPL Stats Website](https://deepnote.com/project/19f51d7b-ae79-4c51-906c-dee0138da144) –– [Docs](https://github.com/sportsdatasolutions/python_project_template/blob/master/getting_started_deepnote.md)\n\n#### _collections, books, journals_\n- [Intro to Deep Learning](https://www.kaggle.com/learn/intro-to-deep-learning) by [Ryan Holbrook](https://www.kaggle.com/ryanholbrook) @ **Kaggle**\n- [Datascience IPython Notebooks](https://github.com/donnemartin/data-science-ipython-notebooks) by [Donne Martin](https://github.com/donnemartin)\n-  [Maths: Form and Function with Python](https://github.com/James-G-Hill/Mathematics-Form-and-Function-Notebooks) by [James G. Hill](https://github.com/James-G-Hill) \n  - [ \u003csub\u003e\u003csub\u003e\u003cimg alt=\"by Peter Norvig\" height=\"20\" src=\"https://deepnote.com/buttons/launch-in-deepnote.svg\"\u003e\u003c/sub\u003e\u003c/sub\u003e](https://deepnote.com/launch?template=data-science\u0026url=https%3A%2F%2Fgithub.com%2FCamDavidsonPilon%2FProbabilistic-Programming-and-Bayesian-Methods-for-Hackers%2Fblob%2Fmaster%2FPrologue%2FPrologue.ipynb) [Probabilistic Programming and Bayesian Methods for Hackers](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers)\n- [ \u003csub\u003e\u003csub\u003e\u003cimg alt=\"by Peter Norvig\" height=\"20\" src=\"https://deepnote.com/buttons/launch-in-deepnote.svg\"\u003e\u003c/sub\u003e\u003c/sub\u003e](https://deepnote.com/launch?template=data-science\u0026url=https%3A%2F%2Fgithub.com%2Funpingco%2FPython-for-Probability-Statistics-and-Machine-Learning-2E%2Fblob%2Fmaster%2Fchapter%2Fmachine_learning%2Fintro.ipynb) [Python for Probability, Statistics, and Machine Learning 2E](https://github.com/unpingco/Python-for-Probability-Statistics-and-Machine-Learning-2E)\n- [ \u003csub\u003e\u003csub\u003e\u003cimg alt=\"by Peter Norvig\" height=\"20\" src=\"https://deepnote.com/buttons/launch-in-deepnote.svg\"\u003e\u003c/sub\u003e\u003c/sub\u003e](https://deepnote.com/launch?template=data-science\u0026url=https%3A%2F%2Fgithub.com%2Fmikhailklassen%2FMining-the-Social-Web-3rd-Edition%2Fblob%2Fmaster%2Fnotebooks%2FChapter%25200%2520-%2520Preface.ipynb) [Mining the Social Web](https://github.com/mikhailklassen/Mining-the-Social-Web-3rd-Edition/tree/master/notebooks) by [Mikhail Klassen](https://github.com/mikhailklassen)\n\n## Integrations\n-  [ColabCode](https://github.com/abhishekkrthakur/colabcode) by [Abhishek Thakur](https://github.com/abhishekkrthakur) –– [Video](https://youtu.be/7kTbM3D02jU)\n\n## Resources\n- [Deepnote Slack Community](https://join.slack.com/t/deepnotecommunity/shared_invite/enQtOTI4OTA1MzYwNTMzLTQ4ZGY4Y2VkOTZkYTNjY2U3NTU5ZjJjMDRiMmNmOTgzMzhmYjZlMTczZmY1MDhhM2RmMDk3OWYxM2MyZmFlMDc)\n-  [Deepnote Launch Buttons](https://github.com/SuNaden/deepnote-launch-example) by [Filip Stollar](https://github.com/SuNaden) \n\n\n## Other Awesome Lists\n - [lists](https://github.com/jnv/lists)\n - [pytudes](https://github.com/norvig/pytudes)\n - [awesome-r](https://github.com/qinwf/awesome-R)\n - [awesome-aws](https://github.com/donnemartin/awesome-aws)\n - [awesome-dataviz](https://github.com/fasouto/awesome-dataviz)\n - [awesome-python](https://github.com/vinta/awesome-python)\n - [awesome-tensorflow](https://github.com/jtoy/awesome-tensorflow)\n - [awesome-datascience](https://github.com/academic/awesome-datascience)\n - [awesome-datascience-ideas](https://github.com/JosPolfliet/awesome-datascience-ideas)\n - [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)\n - [awesome-public-datasets](https://github.com/caesar0301/awesome-public-datasets) \n - [awesome-machine-learning-on-source-code](https://github.com/src-d/awesome-machine-learning-on-source-code)\n - [awesome-graph-classification](https://github.com/benedekrozemberczki/awesome-graph-classification)\n - [awesome-decision-tree-papers](https://github.com/benedekrozemberczki/awesome-decision-tree-papers)\n - [awesome-fraud-detection-papers](https://github.com/benedekrozemberczki/awesome-fraud-detection-papers)\n - [machine-learning-for-software-engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers)\n- [Glossary of common statistics and ML terms](https://www.analyticsvidhya.com/glossary-of-common-statistics-and-machine-learning-terms/) \n\nOther amazingly awesome lists can be found by searching: [#awesome](https://github.com/topics/awesome), [#awesome-lists](https://github.com/topics/awesome-lists)\n\n#### In the media\n\n-  [Deepnote: the modern way to teach Data Science](https://medium.com/@robertlacok/deepnote-the-modern-way-to-teach-data-science-99998ce659a)\n-  [Collaborative notebooks for ML course at Cambridge](https://deepnote.com/article/university-of-cambridge)\n-  [Reviewing Deepnote — The New IDE for Data Scientists](https://towardsdatascience.com/reviewing-deepnote-the-new-ide-for-data-scientists-90c3464ebc5e)\n-  [Deepnote Emerges from Stealth: With YC, Index, and Accel Leading Our Seed Round](https://medium.com/deepnote/deepnote-emerges-from-stealth-with-yc-index-and-accel-leading-our-seed-round-12325281cde0)\n\n### License\n\n[![Creative Commons License](http://i.creativecommons.org/l/by/4.0/88x31.png)](http://creativecommons.org/licenses/by/4.0/)\n\nThis work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/).\n\u003c!--stackedit_data:\neyJoaXN0b3J5IjpbMjcxMjI1NTYyLDMzNzYzOTc5MSwtNjk4Mj\nU2MTU2LC00NjA5NjU5NTcsMTUxMTg3MjY1NiwyMTExOTMzNzE5\nLDczNDYyNzM1OCwtOTA0ODQzOTYsLTk3MDU2Nzc0NywtMTkxMj\nIwMDk1MiwtMTk2MzA5MzkzMiwxMzQ5MzQ4NjE4LC0xNzYwODMy\nOTE0LDkyNDk0NTA5MSwtMTk0Mjg3NDQzLC0xNjcwNjUxMDY0LD\nEyNTQzMjE5MywtMTk3MDMwMTgwLDE5MDA4OTc2OTUsMjEyOTA1\nNzA2NV19\n--\u003e","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/ramene%2Fawesome-deepnote/projects"}