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If you're new to Neuraldemy, start your AI learning journey by [joining our platform](https://neuraldemy.com/subscription) through the Neuraldemy Subscription.\n\n**Unlock The Full Potential:**\n\nWhile we offer these resources for free, consider becoming a paid subscriber for added benefits. Subscribers enjoy the privilege of asking questions, exploring in-depth concepts, and demystifying the mathematics behind these AI black boxes. \n\nJoin Neuraldemy today and become part of a vibrant community passionate about AI education and exploration.\n\n👉 [Neuraldemy Platform](https://neuraldemy.com/)\n\n## How To Use It: \n\nThis repository contains all our free resources related to machine learning created and maintained by Amritesh Kumar. The best way to navigate through these resources is to follow our tutorial available on our website, but they can still be used independently. This repository contains:\n\n1. **ML Tools**: A folder containing all the tools you need to get started in machine learning or deep learning. This section is entirely free, and you must know these libraries to get started in ML.\n\n2. **ML Tutorial**: This folder contains all our free resources related to tutorials (only the practical section, not theory). You can still use them based on your knowledge.\n\n3. **ML Projects**: This folder has some ML projects that you can use to practice and learn ML. However, most of the projects are in another repository (AI Projects).\n\n### Premium Tutorials\n\n1. https://neuraldemy.com/singular-value-decomposition/\n2. https://neuraldemy.com/in-depth-linear-regression-concept-and-application/\n3. https://neuraldemy.com/principal-components-analysis/\n4. https://neuraldemy.com/linear-discriminant-analysis/\n5. https://neuraldemy.com/in-depth-naive-bayes-concept-and-application/\n6. https://neuraldemy.com/in-depth-logistic-regression/\n7. https://neuraldemy.com/support-vector-machines/\n8. https://neuraldemy.com/in-depth-decision-trees-concept-and-application/\n9. https://neuraldemy.com/stochastic-gradient-descent/\n10. https://neuraldemy.com/in-depth-random-forests-ensemble-learning-concept-and-application/\n11. https://neuraldemy.com/nearest-neighbors-concept/\n12. https://neuraldemy.com/shop/clustering-and-outlier-detection/\n13. https://neuraldemy.com/gaussian-mixture-models/\n14. https://neuraldemy.com/deep-learning-introduction-to-anns/\n15. https://neuraldemy.com/convolutional-neural-networks-cnns/\n\nNLP tutorial is coming soon 🔥\n\n### ML Projects\nPractice machine learning and build a portfolio: https://github.com/kelixirr/AI-Projects\n\n### Ask Doubts\n\nIf you are stuck or want to ask something, feel free to visit our community https://neuraldemy.com/community/ and raise your query in the forum. \n\n### Extra Resources\n\nLearn The Basics of Tensorflow 2: https://ryancheunggit.gitbooks.io/tfbook/content/\nMachine learning papers: https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap and https://github.com/terryum/awesome-deep-learning-papers\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkelixirr%2Fneuraldemy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkelixirr%2Fneuraldemy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkelixirr%2Fneuraldemy/lists"}