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Python Cheatsheets ⭐️

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Python Notes ⭐️

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🎥 Free course "Computational Thinking and Data Science"
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👨🏻‍💻 One of the best resources I've found for learning computational thinking and data science is this free course from MIT. It covers concepts like data analysis, computational modeling, and using algorithms to solve complex problems. I've included the links to the slides and videos from the course below:👇

📄 Slides link: Lecture Slides and Files

📹 Video links: Lecture Videos

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👨🏻‍💻 One of the most popular GitHub repositories for "learning and using algorithms in Python" is The Algorithms - Python repo with 196K stars.

✏️ It has a lot of organized and categorized code that you can use to find, read, and run different algorithms. Everything you can think of is here; from simple algorithms like sorting to advanced algorithms for machine learning, artificial intelligence, neural networks, and more.

✅ Why should we use it?

🔢 For learning: If you're looking to learn algorithms in action, this is great.

🔢 For practice: You can take the codes, run them, and modify them to better understand.

🔢 For projects : You can even use the codes here in real-life or academic projects.

🔢 For interviews: If you're preparing for data science interviews, this is full of practical algorithms.


┌ 🏳️‍🌈 The Algorithms - Python
└ 🐱 GitHub-Repos

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15 ways to optimize neural network training

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GANs clearly explained with visuals

This website provides a clear explanation, Try it out yourself: poloclub.github.io/ganlab/

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🪙 Everything you need to get started in machine learning.

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pandas Project: Make a Gradebook With Python & pandas

Link: https://realpython.com/pandas-project-gradebook/

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