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All Resources to Learn Data Science

All Resources to Learn Data Science

Introduction

Welcome to the AI ML Resources category page, where you’ll find a wealth of knowledge on various topics related to Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Mathematics and statistics required to learn Data Science. Each of the pages mentioned below brings together a wide range of articles, tutorials, and guides that delve into the fascinating world of AI and ML. Whether you’re a beginner seeking foundational knowledge or an experienced practitioner looking to expand your skills, these resources offer valuable insights and practical guidance. You need to go through these links one at time. As a master page you can book mark this page.

Resources to Learn Everything about Data Science, AI, Machine Learning, Deep Learning and NLP.

  1. Best-Youtube-Channels-to-Learn-Data Science.md : 90+ YouTube channels to learn Data Science, Machine Learning, Deep Learning, NLP, Data Engineering, Data Analysis, Bigdata, Programming, Statistics, Mathematics. These channels are run, managed, owned by universities or individuals, who industry stalwarts in the respective field.
  2. Data Science-Books.md : This link contains excellent presentations Book, (PPT), Handbook, Report, Articles (ARTC), Book, Booklet, eBook, Notebook, Notes, GUIDE, TOC, Syllabus, LINKS, Handbook, Chapter, Tool, BROC – Broacher on Machine Learning, Deep Learning, NLP, Statistics, Reinforcement Learning, GAN. 550+ pdf files, 400+ books.
  3. Data Science Cheatsheets.md : 140+ cheatsheets on ML, DL, DE, DA, NLP, Algorithms, Pandas, Numpy, Dask, Bigdata, Statistics, Python, SQL, Docker, sklearn, git, GNN etc.
  4. AI ML Conferences and Journals.md : A list of 30+ AI conferences and journals related to AI, NLP, Deep Learning. Almost all major happening in the world of AI/ML is presented in these conferences and published in these magazines.
  5. Best Resources to Learn Python.md : Many resource including books, jupyter notebooks, github repos, python libraries, websites/blogs.
  6. Data Scientists and AI ML Researchers.md : 100+ world class researchers in AI/ML, they are working with different Universities and Corporations.
  7. DS AI ML Online Course Tutorial Videos.md : Hundreds of courses, tutorial, video lecture series to learn Data Science, AI, ML topics online
  8. Reinforcement Learning Repositories.md
  9. Data Science Interview Question Answers
  10. Important AI Research Papers : By this time there are thousands, if not millions, papers in AI and related technologies. I found around 50 paper of special interest. You may be interested in reading these.
  11. High School Maths for Data Science.md
  12. Basic Statistics for Data Science.md : Important Web-pages and websites to learn statistics.
  13. Mathematics-in-Data-Science.md :
  14. My Daily Tools.md : 200+ Tools for Blogging, Bookmarking, Business Development, Clip Art, Image & Photo Sharing Platforms, Creative Thinking, Data in Cloud, Development, File Converter, Free ebook, Learn Drawing, Mass Mailing, Misc-Tools, Notes Taking, Online Audio, Online Training, Research, Screencapture & Screencasting Tools, Sharing, Skill Testing, Video and Image Creation, Video Download, Voice Recording, Web Scrapping, Website Content, NLP Work, TTS, Language Sanskrit, Design-FE & UI, SEO/SEM, Language Chinese, Language English, Language Indic, Sanskrit Text
  15. My Favorite Chrome Extensions.md : 32 Highly Valuable Chrome Extension, which I use regularly for my research and regular work.
  16. My AI Learning Diary : This is my personal diary which contains resources, which I know, learned or people have told me to experiment with. I started writing this diary in Mar’ 2019. This diary is related to my work/learning in data science, AI, ML, NLP, DL, GNN etc. Some links related to Project Management are also kept in this diary. The resources here are python library link, blog articles, youtube article, AI products, architecture, images etc. As of 12-Dec-22, the size of this diary is around 392 page.
  17. ML Frameworks Libraries Tools.md : A list of 600 data science libaries (mostly python), frameworks, IDE, cloud, AutoML, MLOPs, CI/CD, NLP, Deep Learning, Timeseries, GAN, Package Management, Transformers, GNN.
  18. AI ML Blogs.md : 370+ blogs/website, who publishes articles, research, opinions, observations related to AI, ML, DL, Signal Processing, Computer Vision, Text Processing, Audio Processing, Image/video/Audio/Text Generation on regular basis.
  19. Data Sources.md : 200+ Data Sources, Databases, and ETL Tools. Data generated by different systems can be structured or unstructured. It can be OLTP, OLAP, Audio, Video, Images, Key-Value pair, text books/articles, graph, map etc. There are different databases to store different kind of data. These databases has different features to handle different scale of data, take care of security, performance and ETL tasks.
  20. Datasets.md : 200+ dataset sources and important dataset for Classical Machine Learning, Computer Vision, NLP/NLU, Audio Processing, Time Series related projects.
  21. Deep Learning Tasks and Models.md : Deep Learning, NLP Tasks related model and datasets.
  22. AI Conference.md
  23. Github Repos for Data Science

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