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https://github.com/d2l-ai/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
https://github.com/d2l-ai/d2l-en
book computer-vision data-science deep-learning gaussian-processes hyperparameter-optimization jax kaggle keras machine-learning mxnet natural-language-processing notebook python pytorch recommender-system reinforcement-learning tensorflow
Last synced: 11 days ago
JSON representation
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
- Host: GitHub
- URL: https://github.com/d2l-ai/d2l-en
- Owner: d2l-ai
- License: other
- Created: 2018-10-09T01:04:37.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2024-08-18T08:02:36.000Z (3 months ago)
- Last Synced: 2024-10-20T11:13:12.898Z (19 days ago)
- Topics: book, computer-vision, data-science, deep-learning, gaussian-processes, hyperparameter-optimization, jax, kaggle, keras, machine-learning, mxnet, natural-language-processing, notebook, python, pytorch, recommender-system, reinforcement-learning, tensorflow
- Language: Python
- Homepage: https://D2L.ai
- Size: 303 MB
- Stars: 23,549
- Watchers: 416
- Forks: 4,319
- Open Issues: 140
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome - d2l-ai/d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge. (Python)
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- awesome-cv - d2l-en - framework code, math, and discussions. Adopted at 200 universities (Misc / Tags: Object Classification `[ObjCls]`, Object Detection `[ObjDet]`, Object Segmentation `[ObjSeg]`, General Library `[GenLib]`, Text Reading / Object Character Recognition `[OCR]`, Action Recognition `[ActRec]`, Object Tracking `[ObjTrk]`, Data Augmentation `[DatAug]`, Simultaneous Localization and Mapping `[SLAM]`, Outlier/Anomaly/Novelty Detection `[NvlDet]`, Content-based Image Retrieval `[CBIR]`, Image Enhancement `[ImgEnh]`, Aesthetic Assessment `[AesAss]`, Explainable Artificial Intelligence `[XAI]`, Text-to-Image Generation `[TexImg]`, Pose Estimation `[PosEst]`, Video Matting `[VidMat]`, Eye Tracking `[EyeTrk]`)