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๐Ÿฐ๐Ÿณ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ณ๐˜‚๐—น๐—น๐˜† ๐—–๐˜‚๐—ฟ๐—ฎ๐˜๐—ฒ๐—ฑ ๐—–๐—ต๐—ฒ๐—ฎ๐˜๐˜€๐—ต๐—ฒ๐—ฒ๐˜๐˜€ ๐—ฌ๐—ผ๐˜‚'๐—น๐—น ๐—˜๐˜ƒ๐—ฒ๐—ฟ ๐—ก๐—ฒ๐—ฒ๐—ฑ! ๐Ÿ“š

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๐Ÿฐ๐Ÿณ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ณ๐˜‚๐—น๐—น๐˜† ๐—–๐˜‚๐—ฟ๐—ฎ๐˜๐—ฒ๐—ฑ ๐—–๐—ต๐—ฒ๐—ฎ๐˜๐˜€๐—ต๐—ฒ๐—ฒ๐˜๐˜€ ๐—ฌ๐—ผ๐˜‚'๐—น๐—น ๐—˜๐˜ƒ๐—ฒ๐—ฟ ๐—ก๐—ฒ๐—ฒ๐—ฑ! ๐Ÿ“š

This resource list contains 47 carefully curated cheat sheets, documentation, tutorials, and references that cover a wide range of topics relevant to data science, machine learning, and software development. Whether you're a beginner or an experienced practitioner, you'll find something valuable here to help you enhance your skills, streamline your workflow, and stay up-to-date with the latest technologies and best practices. The list includes popular programming languages such as Python and R, data processing and visualization tools like Pandas, NumPy, Matplotlib, and Seaborn, as well as machine learning frameworks like TensorFlow, Keras, PyTorch, and Scikit-learn. You'll also find resources related to databases (SQL, PostgreSQL, MySQL, MongoDB), cloud computing platforms (AWS, Azure, Google Cloud), containerization technologies (Docker, Kubernetes), web development frameworks (Flask, Django), and mathematical foundations (calculus, linear algebra, probability). Additionally, there are cheat sheets and documentation related to NLP, neural networks, deep learning, Apache Spark, Hadoop, regular expressions, and Unix/Linux permissions. Finally, there are references to OpenAI's GPT-3 technology, including cheat sheets and documentation, as well as a cheat sheet for the ChatGPT language model.

  1. Python : https://lnkd.in/grD8XUS6
  2. Pandas : https://lnkd.in/g4yTJ7CP
  3. NumPy : https://lnkd.in/gg9Uw-km
  4. Matplotlib https://lnkd.in/gahrGicD
  5. Seaborn https://lnkd.in/gcu4UKpw
  6. Scikit-learn https://lnkd.in/gGfkNu5i
  7. TensorFlow : https://lnkd.in/g3fw3uRV
  8. Keras : https://lnkd.in/gfPTfbgg
  9. PyTorch https://bit.ly/3lnsiIz
  10. SQL : https://lnkd.in/gnwe4qcb
  11. R : https://lnkd.in/gEgJ6A8j
  12. Git : https://lnkd.in/gyzhztvH
  13. AWS https://bit.ly/3ZQWMS1
  14. Azure https://bit.ly/42f4N4V
  15. Google Cloud Platform : https://bit.ly/3JJADzv
  16. Docker : https://bit.ly/3Lt2zJe
  17. Kubernetes https://lnkd.in/gjXCT7Mb
  18. Linux Command Line : https://bit.ly/3FtcTgw
  19. Jupyter Notebook https://lnkd.in/g7cPmgHQ
  20. Data Wrangling :https://bit.ly/3TiMibP
  21. Data Visualization : https://lnkd.in/gQ52Jd_J
  22. Statistical Inference https://lnkd.in/grNXVQh5
  23. Probability : https://lnkd.in/gvnWCphc
  24. Linear Algebra : https://lnkd.in/gty6XpVF
  25. Calculus https://lnkd.in/gjhsmsxu
  26. Time Series : https://bit.ly/3Fvuep4
  27. NLP: https://bit.ly/3Fvursm
  28. Neural Network : https://lnkd.in/gThs2AAp
  29. Deep Learning : https://lnkd.in/gVbSPae2
  30. Machine Learning : https://bit.ly/3mZ5Wh3
  31. Apache Spark : https://lnkd.in/ge7Rj-Yr
  32. Hadoop : https://bit.ly/3Lq34DR
  33. Big-O Notation t: https://lnkd.in/gfYqM8WU
  34. Regular Expression : https://lnkd.in/gE9kZTZW
  35. Unix/Linux Permissions https://bit.ly/3ZUfwA8
  36. Python String Formatting https://lnkd.in/gHi26Uk2
  37. Flask : https://lnkd.in/gGzbSTgU
  38. Django : https://lnkd.in/grZcWz8y
  39. SQL : https://lnkd.in/gyierV3f
  40. PostgreSQL : https://lnkd.in/gzfiW7zB
  41. MySQL: https://lnkd.in/g4JnPVTe
  42. MongoDB : https://lnkd.in/gHc4F4ER
  43. TensorFlow Probability Cheat Sheet: https://lnkd.in/gr3bgDGP
  44. OpenAI GPT-3 Documentation: https://lnkd.in/gawB_SC9
  45. GPT-3 API Reference: https://lnkd.in/gtCGZvX8
  46. GPT-3 GitHub Repository: https://lnkd.in/g56cQQPD
  47. Chat GPT Cheat Sheet : https://lnkd.in/e43cDB9q

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๐Ÿฐ๐Ÿณ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ณ๐˜‚๐—น๐—น๐˜† ๐—–๐˜‚๐—ฟ๐—ฎ๐˜๐—ฒ๐—ฑ ๐—–๐—ต๐—ฒ๐—ฎ๐˜๐˜€๐—ต๐—ฒ๐—ฒ๐˜๐˜€ ๐—ฌ๐—ผ๐˜‚'๐—น๐—น ๐—˜๐˜ƒ๐—ฒ๐—ฟ ๐—ก๐—ฒ๐—ฒ๐—ฑ! ๐Ÿ“š

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