{"id":19492004,"url":"https://github.com/neelsoumya/butterfly_detector","last_synced_at":"2026-05-12T21:33:27.684Z","repository":{"id":118677999,"uuid":"180774639","full_name":"neelsoumya/butterfly_detector","owner":"neelsoumya","description":"Basic tutorials and code for teaching deep learning and machine learning","archived":false,"fork":false,"pushed_at":"2022-05-18T06:52:25.000Z","size":4013,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-01-08T08:47:17.020Z","etag":null,"topics":["data-science","deep","deep-learning","deep-learning-tutorial","deep-neural-networks","ethical-artificial-intelligence","learning","machine-learning","neural-networks","open","open-data-science","outreach","outreach-activities","public-outreach","statistical-learning","teaching","teaching-materials","teaching-resources","tutorial","tutorials"],"latest_commit_sha":null,"homepage":"https://sites.google.com/site/neelsoumya/research-resources/machine-learning","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/neelsoumya.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-04-11T11:06:28.000Z","updated_at":"2023-07-19T17:04:29.000Z","dependencies_parsed_at":null,"dependency_job_id":"239d592a-16f8-4998-9f78-b02f22537d50","html_url":"https://github.com/neelsoumya/butterfly_detector","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/neelsoumya%2Fbutterfly_detector","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/neelsoumya%2Fbutterfly_detector/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/neelsoumya%2Fbutterfly_detector/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/neelsoumya%2Fbutterfly_detector/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/neelsoumya","download_url":"https://codeload.github.com/neelsoumya/butterfly_detector/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240738093,"owners_count":19849546,"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":["data-science","deep","deep-learning","deep-learning-tutorial","deep-neural-networks","ethical-artificial-intelligence","learning","machine-learning","neural-networks","open","open-data-science","outreach","outreach-activities","public-outreach","statistical-learning","teaching","teaching-materials","teaching-resources","tutorial","tutorials"],"created_at":"2024-11-10T21:19:02.065Z","updated_at":"2026-05-12T21:33:27.639Z","avatar_url":"https://github.com/neelsoumya.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# butterfly_detector\n\nThis is a repository which has tutorials, scripts and notes for teaching machine learning and deep learning. This material can be used to teach machine learning to a general audience and/or working professionals.\n\nThis repository also has materials for outreach and teaching AI to the general public.\n\n\n* Material\n\n    * https://sites.google.com/site/neelsoumya/research-resources/machine-learning\n       \n    * https://github.com/neelsoumya/butterfly_detector\n    \n* Prerequisities (for learning basic statistics)\n\n    * https://sites.google.com/site/neelsoumya/research-resources/basic-statistics  \n    \n    * https://github.com/neelsoumya/basic_statistics\n    \n* Deep learning animation\n\n    * https://playground.tensorflow.org/\n    \n* Deep learning tutorial by Michael Nielsen\n\n    * http://neuralnetworksanddeeplearning.com/\n\n* Deep learning book where each chapter is an executable notebook\n\n    * http://d2l.ai/\n    \n* Tutorial and courses on tensorflow and Google colab\n\n    * https://www.coursera.org/learn/introduction-tensorflow/\n    \n    * https://github.com/lmoroney/dlaicourse\n    \n    * https://colab.research.google.com/github/lmoroney/dlaicourse/blob/master/Course%201%20-%20Part%206%20-%20Lesson%202%20-%20Notebook.ipynb#scrollTo=9FGsHhv6JvDx\n    \n    * https://www.coursera.org/learn/convolutional-neural-networks-tensorflow/\n    \n\n* Course on AI by Prof. Patrick Winston\n\n   * https://www.youtube.com/watch?v=TjZBTDzGeGg\n   \n    \n* Review paper on machine learning\n\n    * https://www.sciencedirect.com/science/article/pii/S0370157319300766#sec9\n    \n* Machine learning course for developers by Google Education\n\n    * https://developers.google.com/machine-learning/crash-course/ml-intro\n    \n* Picture of butterfly taken by my mother Kalyani Banerjee\n\n    * https://www.deviantart.com/kalyanibanerjee/art/Broken-wings-776029085\n    \n    \n    \n* Tensorflow in the browser\n\n    * https://github.com/tensorflow/tfjs/blob/master/GALLERY.md\n\n    * https://coconet.glitch.me/\n\n    * http://cabreraalex.com/interactive-classification/\n    \n    * https://github.com/poloclub/ganlab/\n    \n    * https://www.tensorflow.org/js/demos/\n    \n    * https://experiments.withgoogle.com/collection/creatability\n    \n\n\n* More AI in the browser and outreach materials\n\n    * http://projector.tensorflow.org/\n    \n    * https://experiments.withgoogle.com/collection/ai\n    \n    * https://teachablemachine.withgoogle.com/\n    \n    * https://quickdraw.withgoogle.com/\n    \n    * https://magenta.tensorflow.org/assets/sketch_rnn_demo/index.html\n    \n    * https://pair-code.github.io/what-if-tool/uci.html\n    \n    * https://www.climbproject.org.uk/big-data\n    \n    * https://www.climbproject.org.uk/dance-mat\n    \n    \n* Materials for AI outreach for general public\n\n    * https://www.coursera.org/learn/ai-for-everyone/lecture/9n83j/more-examples-of-what-machine-learning-can-and-cannot-do​\n\n    * https://teachablemachine.withgoogle.com/\n\n    * https://playground.tensorflow.org\n\n    * http://projector.tensorflow.org/\n\n\n* Here are also some other teaching resources I have compiled/designed\n\n    * https://github.com/neelsoumya/butterfly_detector\n    \n    * https://ncase.me/neurons/\n    \n\n* Tensorflow hub\n\n    * http://tfhub.dev/\n    \n\n* Art classification, generation and visualization\n\n    * https://artsexperiments.withgoogle.com/tsnemap/#2611.40,171.15,4110.41,2681.01,0.00,4057.88\n    \n    * https://artsexperiments.withgoogle.com/artpalette/colors/f1e3e5-3b614a-d0a468-f45d53-64a67e\n\n\n* More teaching resources for machine learning\n\n    * https://osf.io/25gnz/\n    \n    * https://sites.google.com/site/neelsoumya/teaching\n    \n    * https://sites.google.com/site/neelsoumya/research-resources/machine-learning\n\n\n* Teaching resources for hierarchical Bayesian models and Bayesian linear regression\n\n    * https://osf.io/ujydr/\n    \n    \n* Another deep learning book\n\n    * http://d2l.ai/?fbclid=IwAR3gOYDbWBpldmwExcZLakejfQsF6Ixo6BmKcspz4eqVMuTRkVv89i-etak\n    \n\n* More tensorflow resources\n\n    * https://www.youtube.com/watch?v=oXj6ew5ymhM\n    \n\n* Rules of machine learning and data science\n\n    * https://www.youtube.com/watch?v=VfcY0edoSLU\n    \n    * https://developers.google.com/machine-learning/guides/rules-of-ml/\n    \n    * https://dl.acm.org/citation.cfm?id=2347755\n    \n    Structuring machine learning projects\n    \n    * https://www.coursera.org/learn/machine-learning-projects\n    \n    \n    Data science in a company \n    \n    * https://cultivating-algos.stitchfix.com/\n    \n    \n* Backpropagation lectures by Andrej Karpathy and Andrew Ng\n\n    * https://www.youtube.com/watch?v=i94OvYb6noo\n    \n    * https://www.coursera.org/learn/machine-learning/home/week/5\n\n\n* Beautiful explanation, game and video on neural networks\n\n    * https://ncase.me/neurons/\n    \n    \n* Communication skills\n\n    * Business skills\n    \n    * Case studies\n    \n    * Business processes\n    \n    * Trans-disciplinarity\n    \n         * https://medium.com/@miekevanderbijl/transdisciplinary-innovation-and-design-d19d1520ddca\n    \n    * How to speak by Prof. Patrick Winston\n    \n         * https://www.youtube.com/watch?v=Unzc731iCUY\n\n* Bayesian methods and great tutorial on logistic regression\n\n    * http://cbl.eng.cam.ac.uk/pub/Public/Turner/News/slides.pdf\n    \n\n* Reinforcement learning\n\n    * https://www.coursera.org/learn/practical-rl/home/welcome\n    \n    * gym_interface.ipynb\n    \n    * gym_interface.py\n    \n* Graph neural networks    \n    \n    * Introduction to graph neural networks\n\n         * https://www.youtube.com/watch?v=uF53xsT7mjc\n\n    * https://github.com/neelsoumya/butterfly_detector/blob/master/graph_neural_networks_tutorial_shortest_path.ipynb\n\n    * DGL library\n\n       * https://github.com/dmlc/dgl\n\n       * https://docs.dgl.ai/tutorials/blitz/index.html  \n    \n    \n    \n* Very good tutorial on neural networks, autoencoder, softmax \n\n    * https://www.youtube.com/watch?v=VrMHA3yX_QI\n    \n\n* Natural language processing\n\n    * https://www.coursera.org/learn/natural-language-processing-tensorflow/home/welcome\n    \n    * https://github.com/neelsoumya/nlp_resources\n    \n    * gpt2_playground.ipynb\n    \n    \n* Basics of statistical learning from the Introduction to Statistical Learning (ISLR) text (videos and text)\n\n    * https://www.statlearning.com/s/ISLR-Seventh-Printing.pdf\n    \n    * https://www.youtube.com/playlist?list=PLOg0ngHtcqbPTlZzRHA2ocQZqB1D_qZ5V\n    \n    * http://www.statlearning.com/\n    \n    \n* Basics of statistics\n \n    * https://www.openintro.org/stat/textbook.php?stat_book=aps\n\n\n* AI podcast by Lex Freidman\n\n    * https://www.youtube.com/watch?v=vNOTDn3D_RI\u0026list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4\n    \n    \n* Link for citation (if you like this work, please cite it as)\n\n    * Soumya Banerjee. (2020, January 22). neelsoumya/butterfly_detector: Open source teaching materials for machine learning (Version v1.0). Zenodo. http://doi.org/10.5281/zenodo.3621363\n\n    * [![DOI](https://zenodo.org/badge/180774639.svg)](https://zenodo.org/badge/latestdoi/180774639)\n\n\n    \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fneelsoumya%2Fbutterfly_detector","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fneelsoumya%2Fbutterfly_detector","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fneelsoumya%2Fbutterfly_detector/lists"}