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Data Science Cheat Sheets
Quick help to make a data scientist's life easier

About Dataset
A collection of cheat sheets for various data-science related languages and topics


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💡 #deeplearning #AI #ML #python

Data Science Cheat Sheets
Quick help to make a data scientist's life easier ✅

http://t.me/codeprogrammer 🔒

💡 #deeplearning #AI #ML #python

Quick Python cheatsheet.

https://t.me/DataScience4 ⭐️

IP Address Information using Python

Is it useful to you ❓

📂 Tags: #coding #Python

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How Python work in our computer clearly explained

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When invoking a Python script, you can specify various options/flags for better flexibility.

Here are 9 of the most commonly used options.

🔷 𝐩𝐲𝐭𝐡𝐨𝐧 -𝐜: Run a single Python command.
🔷 𝐩𝐲𝐭𝐡𝐨𝐧 -i: Run the script as usual and enter the interactive model instead of exiting.
🔷 𝐩𝐲𝐭𝐡𝐨𝐧 -𝐎: Ignore assert statements (This is alphabet ‘O’).
🔷 𝐩𝐲𝐭𝐡𝐨𝐧 -𝐎𝐎: Ignore assert statements and discard docstrings.
🔷 𝐩𝐲𝐭𝐡𝐨𝐧 -𝐖: Ignore all warnings.
🔷 𝐩𝐲𝐭𝐡𝐨𝐧 -𝐦: Run a module as a script.
🔷 𝐩𝐲𝐭𝐡𝐨𝐧 -𝐯: Enter verbose mode.
🔷 𝐩𝐲𝐭𝐡𝐨𝐧 -𝐱: Skip the first line.
🔷 𝐩𝐲𝐭𝐡𝐨𝐧 -𝐄: ignore all Python environment variables.

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Convert PDF to docx using Python

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses

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20 Python Libraries You Aren't Using But Should

📕 Book

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👩‍💻 TheAlgorithms/Python is a collection of algorithms written in Python. It is an open source project where developers from all over the world contribute with various algorithms used in computer science, mathematics, and data science.

🔍 The repository includes hundreds of algorithm implementations in various categories, such as:

🌟 Sorting and searching (e.g. quicksort, binary search).
🌟 Data structures (e.g. trees, graphs, queues).
🌟 Graph algorithms (e.g. depth-first search, breadth-first search).
🌟 Cryptography (e.g. encryption, hashing).
🌟 Machine learning algorithms and many more!

💡 The goal of the project is to offer a learning resource where developers can learn and understand how different algorithms work. Each algorithm is accompanied by code examples, and many of them have detailed explanations.

🔐 License: MIT

👍 Github

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