Machine Learning
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Real Machine Learning โ€” simple, practical, and built on experience.
Learn step by step with clear explanations and working code.

Admin: @HusseinSheikho || @Hussein_Sheikho
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Here's a Python tool for accurately extracting text from PDFs and images into Markdown and JSON. ๐Ÿ“„โœจ

It supports tables, formulas, multiple OCR engines (Marker, Surya-OCR, Tesseract) and has built-in personal data removal. ๐Ÿ”’๐Ÿค–

https://github.com/CatchTheTornado/pdf-extract-api

#PDF #OCR #Python #Markdown #DataExtraction #TechTools

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Foundations of Applied Mathematics is a free series of four textbooks created for the applied and computational mathematics program at Brigham Young University. ๐Ÿ“š

The series includes four volumes:
*   Mathematical Analysis
*   Algorithms, Approximation, and Optimization
*   Uncertainty and Data
*   Dynamics and Control

The series is suitable for upper-level undergraduate and introductory graduate students. It also includes Python lab exercises and practical assignments, connecting mathematical theory with numerical computation, algorithms, data analysis, and scientific applications. ๐Ÿ

I particularly appreciate that these are not just theoretical textbooks. The accompanying Python materials help to illustrate how these concepts are applied to real-world computational problems. ๐Ÿ’ป

https://foundations-of-applied-mathematics.github.io

#Mathematics #Python #Education #DataScience #Algorithms #Learning

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A Powerful Alternative to Pandas ๐Ÿš€

This is an optimized replacement for Pandas that can significantly speed up data processing without requiring major changes to your code. โš™๏ธ

To get started, simply replace a single import:

import fireducks.pandas as pd

Performance Benchmarks demonstrate speed improvements in various use cases. ๐Ÿ“ˆ

More: https://colab.research.google.com/drive/1UIokuJ4cytoiVSabRDqcziDXOan8bVua?usp=sharing

#Pandas #Python #DataScience #Performance #Fireducks #BigData

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๐Ÿ”– Learning Data Science through interactive examples

One of the most useful repositories for those who want to better understand machine learning.

It transforms complex concepts into visual experiments: you can study models, change parameters, and immediately see the results.

โ›“ Link to GitHub
https://github.com/GeostatsGuy/DataScienceInteractivePython

#DataScience #MachineLearning #Python #Learning #Tech #GitHub

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Python And Flask Framework Complete Course

Python-Powered Proficiency: Depth Introduction To Python Programming And Python Web Framework Flask.โ€ฆ

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A Collection of Machine Learning Libraries for Python ๐Ÿค–

A large repository containing over 900 libraries and frameworks for machine learning. ๐Ÿ“š

All projects are sorted by quality and popularity, which helps you quickly find the best tools for working with AI and ML. โš™๏ธ

Repo: https://github.com/ml-tooling/best-of-ml-python?tab=readme-ov-file#vector-similarity-search-ann

#MachineLearning #Python #AI #DataScience #MLTools #Programming

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๐Ÿ“š "Mathematical Methods in Data Science with Python" by Sebastian Roche.

๐Ÿ”— https://mmids-textbook.github.io

#Python #DataScience #MachineLearning #Mathematics #Programming #Learning

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Cheat sheet for Scapy: creating and configuring packets, working with IP addresses, sending and receiving packets, sniffing traffic, fuzzing, and viewing packet structure. ๐Ÿ“ฆ๐Ÿ”

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