Hacker News
- Awesome machine learning https://github.com/josephmisiti/awesome-machine-learning 10 comments
- Machine Learning frameworks, libraries and software https://github.com/josephmisiti/awesome-machine-learning 35 comments
Lobsters
- A curated list of Machine Learning frameworks, libraries and software https://github.com/josephmisiti/awesome-machine-learning 2 comments compsci
- Awesome Machine Learning is missing Haskell libraries. BTW, what's the state of Haskell machine learning libraries compared to Julia ones? Is there a lot of development done? https://github.com/josephmisiti/awesome-machine-learning 11 comments haskell
Linking pages
- GitHub - ZuzooVn/machine-learning-for-software-engineers: A complete daily plan for studying to become a machine learning engineer. https://github.com/ZuzooVn/machine-learning-for-software-engineers/blob/master/README.md 111 comments
- GitHub - kuchin/awesome-cto: A curated and opinionated list of resources for Chief Technology Officers, with the emphasis on startups https://github.com/kuchin/awesome-cto 85 comments
- GitHub - sindresorhus/awesome: 😎 Awesome lists about all kinds of interesting topics https://github.com/sindresorhus/awesome 69 comments
- GitHub - bayandin/awesome-awesomeness: A curated list of awesome awesomeness https://github.com/bayandin/awesome-awesomeness 66 comments
- GitHub - dive-into-machine-learning/dive-into-machine-learning: Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.) https://github.com/hangtwenty/dive-into-machine-learning 39 comments
- GitHub - vinta/awesome-python: A curated list of awesome Python frameworks, libraries, software and resources https://github.com/vinta/awesome-python 38 comments
- GitHub - owainlewis/awesome-artificial-intelligence: A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers. https://github.com/owainlewis/awesome-artificial-intelligence 35 comments
- GitHub - jnv/lists: The definitive list of lists (of lists) curated on GitHub and elsewhere https://github.com/jnv/lists 28 comments
- GitHub - jbhuang0604/awesome-computer-vision: A curated list of awesome computer vision resources https://github.com/jbhuang0604/awesome-computer-vision 17 comments
- GitHub - huangsam/ultimate-python: Ultimate Python study guide for newcomers and professionals alike. https://github.com/huangsam/ultimate-python 16 comments
- GitHub - zhimin-z/awesome-awesome-artificial-intelligence: A curated list of awesome curated lists of many topics closely related to artificial intelligence. https://github.com/zhimin-z/awesome-awesome-artificial-intelligence 15 comments
- 100+ Best Machine Learning Blogs For Beginners https://www.theinsaneapp.com/2021/04/top-machine-learning-blogs-to-follow-in-2021.html 13 comments
- GitHub - kiloreux/awesome-robotics: A list of awesome Robotics resources https://github.com/Kiloreux/awesome-robotics 13 comments
- GitHub - ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code: 500 AI Machine learning Deep learning Computer vision NLP Projects with code https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code 13 comments
- 25 Open-Source Machine Learning Repos to Inspire Your Next Project | by Khoa Pham | Heartbeat https://heartbeat.fritz.ai/25-open-source-machine-learning-repos-to-inspire-your-next-project-3b027a90155 7 comments
- GitHub - Somnibyte/MLKit: A simple machine learning framework written in Swift 🤖 https://github.com/somnibyte/mlkit 6 comments
- GitHub - MaxHalford/eaopt: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution) https://github.com/maxhalford/eaopt 5 comments
- 100+ Best GitHub Repositories For Machine Learning https://www.theinsaneapp.com/2021/09/best-github-repository-for-machine-learning.html 3 comments
- Anomaly detection in Python using the pyod library - The Data Scientist https://thedatascientist.com/anomaly-detection-in-python-using-the-pyod-library/ 2 comments
- GitHub - floydwch/the-most-influential-developers-on-github: For Github Data Challenge 2014 https://github.com/floydsoft/the-most-influential-developers-on-github 2 comments
Linked pages
- GitHub - tensorflow/swift: Swift for TensorFlow https://github.com/tensorflow/swift 439 comments
- Chart.js | Open source HTML5 Charts for your website https://www.chartjs.org/ 388 comments
- CHICKEN Scheme http://www.call-cc.org/ 314 comments
- GitHub - milvus-io/milvus: Vector database for scalable similarity search and AI applications. https://github.com/milvus-io/milvus 145 comments
- GitHub - karpathy/neuraltalk: NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences. https://github.com/karpathy/neuraltalk 143 comments
- GitHub - neuml/txtai: 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows https://github.com/neuml/txtai 138 comments
- Stan - Stan https://mc-stan.org/ 127 comments
- Vector database - Milvus https://milvus.io/ 121 comments
- Interactive javascript charts library http://www.highcharts.com 112 comments
- GitHub - nidhaloff/igel: a delightful machine learning tool that allows you to train, test, and use models without writing code https://github.com/nidhaloff/igel/tree/master 108 comments
- GitHub - google/jax: Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more https://github.com/google/jax 99 comments
- GitHub - nebuly-ai/nebullvm: Plug and play modules to optimize the performances of your AI systems 🚀 https://github.com/nebuly-ai/nebullvm 98 comments
- GitHub - harthur/brain: [UNMAINTAINED] Simple feed-forward neural network in JavaScript https://github.com/harthur/brain 97 comments
- C3.js | D3-based reusable chart library http://c3js.org/ 95 comments
- SciRuby http://sciruby.com/ 91 comments
- Shiny http://shiny.rstudio.com/ 89 comments
- GitHub - CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers: aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;) https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers 89 comments
- ROOT: analyzing petabytes of data, scientifically. - ROOT https://root.cern.ch/ 84 comments
- SimpleCV http://www.simplecv.org/ 84 comments
- Sigma.js http://sigmajs.org/ 82 comments
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