Machine Learning with Python
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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.

Admin: @HusseinSheikho || @Hussein_Sheikho
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python-interview-questions.pdf
1.2 MB
100 Python Interview Questions and Answers

This book is a practical guide to mastering Python interview preparation. It contains 100 carefully curated questions with clear, concise answers designed in a quick-reference style.

#Python #PythonTips #PythonProgramming

https://t.me/CodeProgrammer
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Tip for clean code in Python:

Use Dataclasses for classes that primarily store data. The @dataclass decorator automatically generates special methods like __init__(), __repr__(), and __eq__(), reducing boilerplate code and making your intent clearer.

from dataclasses import dataclass

# --- BEFORE: Using a standard class ---
# A lot of boilerplate code is needed for basic functionality.

class ProductOld:
def __init__(self, name: str, price: float, sku: str):
self.name = name
self.price = price
self.sku = sku

def __repr__(self):
return f"ProductOld(name='{self.name}', price={self.price}, sku='{self.sku}')"

def __eq__(self, other):
if not isinstance(other, ProductOld):
return NotImplemented
return (self.name, self.price, self.sku) == (other.name, other.price, other.sku)

# Example Usage
product_a = ProductOld("Laptop", 1200.00, "LP-123")
product_b = ProductOld("Laptop", 1200.00, "LP-123")

print(product_a) # Output: ProductOld(name='Laptop', price=1200.0, sku='LP-123')
print(product_a == product_b) # Output: True


# --- AFTER: Using a dataclass ---
# The code is concise, readable, and less error-prone.

@dataclass(frozen=True) # frozen=True makes instances immutable
class Product:
name: str
price: float
sku: str

# Example Usage
product_c = Product("Laptop", 1200.00, "LP-123")
product_d = Product("Laptop", 1200.00, "LP-123")

print(product_c) # Output: Product(name='Laptop', price=1200.0, sku='LP-123')
print(product_c == product_d) # Output: True


#Python #CleanCode #ProgrammingTips #SoftwareDevelopment #Dataclasses #CodeQuality

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By: @CodeProgrammer โœจ
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Forwarded from Machine Learning
๐Ÿ“Œ PyTorch Tutorial for Beginners: Build a Multiple Regression Model from Scratch

๐Ÿ—‚ Category: DEEP LEARNING

๐Ÿ•’ Date: 2025-11-19 | โฑ๏ธ Read time: 14 min read

Dive into PyTorch with this hands-on tutorial for beginners. Learn to build a multiple regression model from the ground up using a 3-layer neural network. This guide provides a practical, step-by-step approach to machine learning with PyTorch, ideal for those new to the framework.

#PyTorch #MachineLearning #NeuralNetwork #Regression #Python
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Comprehensive Python Cheatsheet.pdf
6.3 MB
Comprehensive Python Cheatsheet

This Comprehensive #Python Cheatsheet brings together core syntax, data structures, functions, #OOP, decorators, regular expressions, libraries, and more โ€” neatly organized for quick reference and deep understanding.

https://t.me/CodeProgrammer
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All Cheat Sheets Collection (3).pdf
2.7 MB
Python For Data Science Cheat Sheet

#python #datascience #DataAnalysis

https://t.me/CodeProgrammer

React โ™ฅ๏ธ for more amazing content
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Numpy @CodeProgrammer.pdf
2.4 MB
๐Ÿท Sections of the ยซNumPyยป library
โฌ…๏ธ From introductory to advanced


๐Ÿ‘จ๐Ÿปโ€๐Ÿ’ป This is a long-term project to learn Python and NumPy from scratch. The main task is to handle numerical #data and #arrays in #Python using NumPy, and many other libraries are also used.


โœ๏ธ This section shows a structured and complete path for learning #NumPy; but the code examples and exercises help to practically memorize the concepts.


โญ•๏ธ Introduction to NumPy
๐ŸŸ  NumPy arrays
โญ•๏ธ Introduction to array features
๐ŸŸ  Basic operations on arrays
โญ•๏ธ Functions for statistical and aggregative purposes
๐ŸŸ  And...

https://t.me/CodeProgrammer โ›ˆโšก๏ธ
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Mastering pandas%22.pdf
1.6 MB
๐ŸŒŸ A new and comprehensive book "Mastering pandas"

๐Ÿ‘จ๐Ÿปโ€๐Ÿ’ป If I've worked with messy and error-prone data this time, I don't know how much time and energy I've wasted. Incomplete tables, repetitive records, and unorganized data. Exactly the kind of things that make analysis difficult and frustrate you.

โฌ…๏ธ And the only way to save yourself is to use pandas! A tool that makes processes 10 times faster.

๐Ÿท This book is a comprehensive and organized guide to pandas, so you can start from scratch and gradually master this library and gain the ability to implement real projects. In this file, you'll learn:

๐Ÿ”น How to clean and prepare large amounts of data for analysis,

๐Ÿ”น How to analyze real business data and draw conclusions,

๐Ÿ”น How to automate repetitive tasks with a few lines of code,

๐Ÿ”น And improve the speed and accuracy of your analyses significantly.

๐ŸŒ #DataScience #DataScience #Pandas #Python

https://t.me/CodeProgrammer โšก๏ธ
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Real Python.pdf
332 KB
Real Python - Pocket Reference (Important)

#python #py #PythonTips #programming

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The #Python library #PandasAI has been released for simplified data analysis using AI.

You can ask questions about the dataset in plain language directly in the #AI dialogue, compare different datasets, and create graphs. It saves a lot of time, especially in the initial stage of getting acquainted with the data. It supports #CSV, #SQL, and Parquet.

And here's the link ๐Ÿ˜

๐Ÿ‘‰ https://t.me/CodeProgrammer
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I'm happy to announce that freeCodeCamp has launched a new certification in #Python ๐Ÿ

ยป Learning the basics of programming
ยป Project development
ยป Final exam
ยป Obtaining a certificate

Everything takes place directly in the browser, without installation. This is one of the six certificates in version 10 of the Full Stack Developer training program.

Full announcement with a detailed FAQ about the certificate, the course, and the exams
Link: https://www.freecodecamp.org/news/freecodecamps-new-python-certification-is-now-live/

๐Ÿ‘‰ @codeprogrammer
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๐Ÿ“ฑ A collection of videos on PyTorch and neural networks

This is not a full-fledged course with a unified program, but a collection of nine separate videos on PyTorch and neural networks gathered in one playlist.

Inside, there are materials of different levels and formats that are suitable for selective study of topics, practice, and a general understanding of the direction.

What's here:
๐Ÿฎ Introductory videos on PyTorch and the basics of neural networks;

๐Ÿฎ Practical analyses with code writing and project examples;

๐Ÿฎ Materials on computer vision and working with medical images;

๐Ÿฎ Examples of creating chat bots and models on PyTorch;

๐Ÿฎ Analyses of large language models and generative neural networks;

๐Ÿฎ Examples of training agents and reinforcement tasks;

๐Ÿฎ Videos from different authors without a general learning logic.
The collection is suitable for those who are already familiar with Python and want to selectively study PyTorch without a strict study plan โ€” get it here.

https://www.youtube.com/playlist?list=PLp0BA-8NZ4bhBNWvUBPDztbzLar9Jcgd-


tags: #pytorch #DeepLearning #python

โžก @CodeProgrammer
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