{"id":60839,"url":"https://github.com/datascienceid/deep-learning-resources","name":"deep-learning-resources","description":"A curated list of deep learning resources books, courses, papers, libraries, conferences, sample code, and many more.","projects_count":54,"last_synced_at":"2026-06-20T16:00:20.466Z","repository":{"id":44130494,"uuid":"129476561","full_name":"datascienceid/deep-learning-resources","owner":"datascienceid","description":"A curated list of deep learning resources books, courses, papers, libraries, conferences, sample code, and many more.","archived":false,"fork":false,"pushed_at":"2021-08-09T05:59:06.000Z","size":7,"stargazers_count":122,"open_issues_count":0,"forks_count":38,"subscribers_count":8,"default_branch":"master","last_synced_at":"2026-06-03T22:03:06.629Z","etag":null,"topics":["awesome","awesome-list","conference","data-science","dataset","deep-learning","indonesia","lecture","machine-learning","paper","science","tutorial"],"latest_commit_sha":null,"homepage":null,"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/datascienceid.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":"2018-04-14T03:11:57.000Z","updated_at":"2026-06-01T11:59:14.000Z","dependencies_parsed_at":"2022-09-21T08:40:52.382Z","dependency_job_id":null,"html_url":"https://github.com/datascienceid/deep-learning-resources","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/datascienceid/deep-learning-resources","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datascienceid%2Fdeep-learning-resources","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datascienceid%2Fdeep-learning-resources/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datascienceid%2Fdeep-learning-resources/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datascienceid%2Fdeep-learning-resources/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/datascienceid","download_url":"https://codeload.github.com/datascienceid/deep-learning-resources/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datascienceid%2Fdeep-learning-resources/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34576054,"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":"2026-06-20T02:00:06.407Z","response_time":98,"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":"2024-05-15T00:00:17.978Z","updated_at":"2026-06-20T16:00:20.466Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Table of Contents"],"sub_categories":["Libraries","Datasets","Courses","Free Books","Tutorials","Videos and Lectures","Papers","Conferences","Sample Code"],"readme":"# Deep Learning Resources\nA curated list of deep learning resources books, courses, papers, libraries, conferences, sample code, and many more.\n\n## Table of Contents\n* **[Free Books](#free-books)**\n\n* **[Courses](#courses)**\n\n* **[Videos and Lectures](#videos-and-lectures)**\n\n* **[Papers](#papers)**\n\n* **[Tutorials](#tutorials)**\n\n* **[Sample Code](#sample-code)**\n\n* **[Datasets](#datasets)**\n\n* **[Conferences](#conferences)**\n\n* **[Libraries](#libraries)**\n\n### Free Books\n1.  [Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Courville](http://www.deeplearningbook.org/)\n2.  [Deep Learning by Microsoft Research](http://research.microsoft.com/pubs/209355/DeepLearning-NowPublishing-Vol7-SIG-039.pdf)\n3.  [Neural Networks and Deep Learning by  Michael Nielsen](http://neuralnetworksanddeeplearning.com/)\n4.\t[Neuraltalk by Andrej Karpathy](https://github.com/karpathy/neuraltalk)\n\n### Courses\n1.\t[Neural Networks for Machine Learning](https://class.coursera.org/neuralnets-2012-001)\n2.\t[Neural networks class](https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH)\n3.  [Deep Learning Course](http://cilvr.cs.nyu.edu/doku.php?id=deeplearning:slides:start)\n4.  [A.I - Berkeley](https://courses.edx.org/courses/BerkeleyX/CS188x_1/1T2013/courseware/)\n5.  [A.I - MIT](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/)\n6.  [Convolutional Neural Networks for Visual Recognition - Stanford](http://vision.stanford.edu/teaching/cs231n/syllabus.html)\n7.  [Practical Deep Learning For Coders](http://course.fast.ai/)\n8.  [MIT 6.S191 Introduction to Deep Learning](http://introtodeeplearning.com/)\n\n### Videos and Lectures\n1.  [Deep Learning, Self-Taught Learning and Unsupervised Feature Learning](https://www.youtube.com/watch?v=n1ViNeWhC24) by Andrew Ng\n2.  [Recent Developments in Deep Learning](https://www.youtube.com/watch?v=vShMxxqtDDs\u0026amp;index=3\u0026amp;list=PL78U8qQHXgrhP9aZraxTT5-X1RccTcUYT) by Geoff Hinton\n3.  [The Unreasonable Effectiveness of Deep Learning](https://www.youtube.com/watch?v=sc-KbuZqGkI) by Yann LeCun\n4.  [Deep Learning of Representations](https://www.youtube.com/watch?v=4xsVFLnHC_0) by Yoshua bengio\n5.  [Making Sense of the World with Deep Learning](http://vimeo.com/80821560) by Adam Coates \n6.\t[How Deep Neural Networks Work](https://www.youtube.com/watch?v=ILsA4nyG7I0)\n7.\t[MIT 6.S191 Introduction to Deep Learning](https://www.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI)\n\n### Papers\n1.  [ImageNet Classification with Deep Convolutional Neural Networks](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf)\n2.  [Using Very Deep Autoencoders for Content Based Image Retrieval](http://www.cs.toronto.edu/~hinton/absps/esann-deep-final.pdf)\n3.  [Learning Deep Architectures for AI](http://www.iro.umontreal.ca/~lisa/pointeurs/TR1312.pdf)\n4.  [Neural Networks for Named Entity Recognition](http://nlp.stanford.edu/~socherr/pa4_ner.pdf)\n5.\t[Training tricks by YB](http://www.iro.umontreal.ca/~bengioy/papers/YB-tricks.pdf)\n\n### Tutorials\n1.\t[How to Implement the Backpropagation Algorithm From Scratch In Python](https://machinelearningmastery.com/implement-backpropagation-algorithm-scratch-python/)\n2.\t[image classifier using convolutional neural network](http://cv-tricks.com/tensorflow-tutorial/training-convolutional-neural-network-for-image-classification/)\n3.\t[A Beginner’s Guide to Recurrent Networks and LSTMs](https://deeplearning4j.org/lstm.html)\n4.\t[Recurrent Neural Networks Tutorial, Part 1 – Introduction to RNNs](http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/)\n5.\t[Stochastic Gradient Descent (SGD) with Python](https://www.pyimagesearch.com/2016/10/17/stochastic-gradient-descent-sgd-with-python/)\n6.\t[A Guide to Deep Learning in PyTorch](http://belajar.machinelearning.id/panduan/pytorch/)\n7.\t[A Quick Introduction to Neural Networks](https://ujjwalkarn.me/2016/08/09/quick-intro-neural-networks/)\n8.\t[An Intuitive Explanation of Convolutional Neural Networks](https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/)\n\n### Sample Code\n1. [Deep Learning with Python](https://github.com/Apress/deep-learning-w-python)\n2. [Deep Learning with TensorFlow](https://github.com/PacktPublishing/Deep-Learning-with-TensorFlow)\n3. [Fundamentals of Deep Learning](https://github.com/darksigma/Fundamentals-of-Deep-Learning-Book)\n4. [Introduction to Deep Learning Using R](https://github.com/Apress/intro-to-deep-learning-using-r)\n\n### Datasets\n1.  [CIFAR-10 and CIFAR-100](http://www.cs.toronto.edu/~kriz/cifar.html)\n2.  [Google House Numbers](http://ufldl.stanford.edu/housenumbers/) from street view\n3.  [IMAGENET](http://www.image-net.org/)\n4.  [MNIST](http://yann.lecun.com/exdb/mnist/) Handwritten digits\n5.  [Tiny Images](http://groups.csail.mit.edu/vision/TinyImages/) 80 Million tiny images6.\n6.  [Fashion-MNIST](https://github.com/zalandoresearch/fashion-mnist) \n\n### Conferences\n1. [CVPR - IEEE Conference on Computer Vision and Pattern Recognition](http://cvpr2018.thecvf.com)\n2. [AAMAS - International Joint Conference on Autonomous Agents and Multiagent Systems](http://celweb.vuse.vanderbilt.edu/aamas18/)\n3. [IJCAI - \tInternational Joint Conference on Artificial Intelligence](https://www.ijcai-18.org/)\n4. [NIPS - Neural Information Processing Systems](https://nips.cc/Conferences/2018)\n5. [ICLR - International Conference on Learning Representations](https://iclr.cc/)\n\n### Libraries\n1.\t[Tensorflow](https://www.tensorflow.org/)\n21.\t[Keras - A high-level neural networks API running on top of TensorFlow, CNTK, or Theano](http://keras.io)\n1.  [Caffe](http://caffe.berkeleyvision.org/)  \n2.  [Torch7](http://torch.ch/)\n3.  [Theano](http://deeplearning.net/software/theano/)\n32.\t[MXnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning framework](https://github.com/dmlc/mxnet/)\n49.\t[TensorFlow.js - formerly known as deeplearn.js](https://github.com/tensorflow/tfjs-core)\n\n## Contributing\nJika anda ingin berkontribusi dalam github ini, sangat disarankan untuk `Pull Request` namun dengan resource berbahasa indonesia.","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/datascienceid%2Fdeep-learning-resources/projects"}