{"id":13415606,"url":"https://github.com/lexfridman/mit-deep-learning","last_synced_at":"2025-05-15T08:03:14.919Z","repository":{"id":38417677,"uuid":"78313173","full_name":"lexfridman/mit-deep-learning","owner":"lexfridman","description":"Tutorials, assignments, and competitions for MIT Deep Learning related courses.","archived":false,"fork":false,"pushed_at":"2024-01-03T13:54:05.000Z","size":65478,"stargazers_count":10271,"open_issues_count":16,"forks_count":2213,"subscribers_count":638,"default_branch":"master","last_synced_at":"2025-04-14T13:04:48.017Z","etag":null,"topics":["artificial-intelligence","data-science","deep-learning","deep-reinforcement-learning","deep-rl","deeplearning","jupyter-notebooks","machine-learning","mit","neural-networks","segmentation","self-driving-cars","tensorflow","tensorflow-tutorials"],"latest_commit_sha":null,"homepage":"https://deeplearning.mit.edu","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lexfridman.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-01-08T00:52:01.000Z","updated_at":"2025-04-13T09:14:40.000Z","dependencies_parsed_at":"2024-09-24T13:38:51.331Z","dependency_job_id":null,"html_url":"https://github.com/lexfridman/mit-deep-learning","commit_stats":{"total_commits":58,"total_committers":6,"mean_commits":9.666666666666666,"dds":0.2931034482758621,"last_synced_commit":"c5cc240d3482889109c954eeac786522843b0b3a"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lexfridman%2Fmit-deep-learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lexfridman%2Fmit-deep-learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lexfridman%2Fmit-deep-learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lexfridman%2Fmit-deep-learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lexfridman","download_url":"https://codeload.github.com/lexfridman/mit-deep-learning/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254301420,"owners_count":22047901,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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"}},"keywords":["artificial-intelligence","data-science","deep-learning","deep-reinforcement-learning","deep-rl","deeplearning","jupyter-notebooks","machine-learning","mit","neural-networks","segmentation","self-driving-cars","tensorflow","tensorflow-tutorials"],"created_at":"2024-07-30T21:00:50.693Z","updated_at":"2025-05-15T08:03:10.878Z","avatar_url":"https://github.com/lexfridman.png","language":"Jupyter Notebook","readme":"# MIT Deep Learning\n\n\u003ca href=\"https://deeplearning.mit.edu/\"\u003e\u003cimg src=\"https://deeplearning.mit.edu/files/images/mit_deep_learning.png\"\u003e\u003c/a\u003e\n\nThis repository is a collection of tutorials for [MIT Deep Learning](https://deeplearning.mit.edu/) courses. More added as courses progress.\n\n## Tutorial: Deep Learning Basics\n\n\u003ca href=\"https://github.com/lexfridman/mit-deep-learning/blob/master/tutorial_deep_learning_basics/deep_learning_basics.ipynb\"\u003e\u003cimg src=\"https://i.imgur.com/j4FqBuR.gif\"\u003e\u003c/a\u003e\n\nThis tutorial accompanies the [lecture on Deep Learning Basics](https://www.youtube.com/watch?list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf\u0026v=O5xeyoRL95U). It presents several concepts in deep learning, demonstrating the first two (feed forward and convolutional neural networks) and providing pointers to tutorials on the others. This is a good place to start.\n\nLinks: \\[ [Jupyter Notebook](https://github.com/lexfridman/mit-deep-learning/blob/master/tutorial_deep_learning_basics/deep_learning_basics.ipynb) \\]\n\\[ [Google Colab](https://colab.research.google.com/github/lexfridman/mit-deep-learning/blob/master/tutorial_deep_learning_basics/deep_learning_basics.ipynb) \\]\n\\[ [Blog Post](https://medium.com/tensorflow/mit-deep-learning-basics-introduction-and-overview-with-tensorflow-355bcd26baf0) \\]\n\\[ [Lecture Video](https://www.youtube.com/watch?list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf\u0026v=O5xeyoRL95U) \\]\n\n\n## Tutorial: Driving Scene Segmentation\n\n\u003ca href=\"https://github.com/lexfridman/mit-deep-learning/blob/master/tutorial_driving_scene_segmentation/tutorial_driving_scene_segmentation.ipynb\"\u003e\u003cimg src=\"images/thumb_driving_scene_segmentation.gif\"\u003e\u003c/a\u003e\n\nThis tutorial demostrates semantic segmentation with a state-of-the-art model (DeepLab) on a sample video from the MIT Driving Scene Segmentation Dataset.\n\nLinks: \\[ [Jupyter Notebook](https://github.com/lexfridman/mit-deep-learning/blob/master/tutorial_driving_scene_segmentation/tutorial_driving_scene_segmentation.ipynb) \\]\n\\[ [Google Colab](https://colab.research.google.com/github/lexfridman/mit-deep-learning/blob/master/tutorial_driving_scene_segmentation/tutorial_driving_scene_segmentation.ipynb) \\]\n\n## Tutorial: Generative Adversarial Networks (GANs)\n\n\u003ca href=\"https://github.com/lexfridman/mit-deep-learning/blob/master/tutorial_gans/tutorial_gans.ipynb\"\u003e\u003cimg src=\"images/thumb_mushroom_biggan.gif\"\u003e\u003c/a\u003e\n\nThis tutorial explores generative adversarial networks (GANs) starting with BigGAN, the state-of-the-art conditional GAN.\n\nLinks: \\[ [Jupyter Notebook](https://github.com/lexfridman/mit-deep-learning/blob/master/tutorial_gans/tutorial_gans.ipynb) \\]\n\\[ [Google Colab](https://colab.research.google.com/github/lexfridman/mit-deep-learning/blob/master/tutorial_gans/tutorial_gans.ipynb) \\]\n\n## DeepTraffic Deep Reinforcement Learning Competition\n\n\u003ca href=\"https://selfdrivingcars.mit.edu/deeptraffic\"\u003e\u003cimg src=\"images/thumb_deeptraffic.gif\"\u003e\u003c/a\u003e\n\nDeepTraffic is a deep reinforcement learning competition. The goal is to create a neural network that drives a vehicle (or multiple vehicles) as fast as possible through dense highway traffic.\n\nLinks: \\[ [GitHub](https://github.com/lexfridman/deeptraffic) \\] \\[ [Website](https://selfdrivingcars.mit.edu/deeptraffic) \\] \\[ [Paper](https://arxiv.org/abs/1801.02805) \\]\n\n## Team\n\n- [Lex Fridman](https://lexfridman.com)\n- [Li Ding](https://www.mit.edu/~liding/)\n- [Jack Terwilliger](https://www.mit.edu/~jterwill/)\n- [Michael Glazer](https://www.mit.edu/~glazermi/)\n- [Aleksandr Patsekin](https://www.mit.edu/~patsekin/)\n- [Aishni Parab](https://www.mit.edu/~aishni/)\n- [Dina AlAdawy](https://www.mit.edu/~aladawy/)\n- [Henri Schmidt](https://www.mit.edu/~henris/)\n","funding_links":[],"categories":["Jupyter Notebook","Please find below the links to awesome cheat-sheet and resources:","A01_机器学习教程","Deep Learning","Machine learning","Course and Tutorial","Computational"],"sub_categories":["Machine-Learning/Data Science/AI/DL:","3. 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