Machine Learning with Python
@CodeProgrammer
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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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Machine Learning with Python
67.8K subscribers
Machine Learning with Python
Best LLMs Courses

Link: https://www.mltut.com/best-large-language-models-courses/

#MachineLearning #DeepLearning #BigData #Datascience #ML #HealthTech #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents

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Machine Learning with Python
🐼 20 of the most used Pandas + PDF functions

πŸ‘¨πŸ»β€πŸ’» The first time I used Pandas, I was supposed to quickly clean and organize a raw and complex dataset with the help of Pandas functions. Using the groupby function, I was able to categorize the data and get in-depth analysis of customer behavior. Best of all, it was when I used loc and iloc that I could easily filter the data.

βœ”οΈ Since then I decided to prepare a list of the most used Pandas functions that I use on a daily basis. Now this list is ready! In the following, I will introduce 20 of the best and most used Pandas functions:



πŸ³οΈβ€πŸŒˆ read_csv(): Fast data upload from CSV files

πŸ³οΈβ€πŸŒˆ head(): look at the first five rows of the database to start..

πŸ³οΈβ€πŸŒˆ info(): Checking data structure such as data type and empty values.

πŸ³οΈβ€πŸŒˆ describe(): Generate descriptive statistics for numeric columns.

πŸ³οΈβ€πŸŒˆ loc[ ]: accesses rows and columns by label or condition.

πŸ³οΈβ€πŸŒˆ iloc[ ]: Access data by row number.

πŸ³οΈβ€πŸŒˆ merge(): Merge dataframes with common columns.

πŸ³οΈβ€πŸŒˆ groupby(): Grouping for easier analysis.

πŸ³οΈβ€πŸŒˆ pivot_table(): Summarize data in pivot table format.

πŸ³οΈβ€πŸŒˆ to_csv(): Save data as a CSV file.

πŸ³οΈβ€πŸŒˆ pd.concat(): Concatenate multiple dataframes in rows or columns.

πŸ³οΈβ€πŸŒˆ pd.melt(): Convert wide format data to long format.

πŸ³οΈβ€πŸŒˆ pd.pivot_table(): Create a pivot table with multiple levels.

πŸ³οΈβ€πŸŒˆ pd.cut(): Split the data into specific intervals.

πŸ³οΈβ€πŸŒˆ pd.qcut(): Sort data by percentage.

πŸ³οΈβ€πŸŒˆ pd.merge(): Merge data in database style for advanced linking.

πŸ³οΈβ€πŸŒˆ DataFrame.apply(): Apply a custom function to the data.

πŸ³οΈβ€πŸŒˆ DataFrame.groupby(): Analyze grouped data.

πŸ³οΈβ€πŸŒˆ DataFrame.drop_duplicates(): Drop duplicate rows.

πŸ³οΈβ€πŸŒˆ DataFrame.to_excel(): Save data directly to Excel file.


β”Œ 🐼 Pandas Functions
β”” πŸ“„ PDF

#MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents

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Machine Learning with Python
Regression & Classification Loss Functions

#MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents

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Machine Learning with Python
Python Network Programming Cheat Sheet πŸ–₯

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Machine Learning with Python
Git commands basics

#MachineLearning #DeepLearning #BigData #Datascience #ML #Pandas #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics #LLMs #AIagents

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Machine Learning with Python
Best Data Analyst Online Certifications!
https://www.mltut.com/data-analyst-online-certification-to-become-a-successful-data-analyst/

#MachineLearning #DeepLearning #BigData #Datascience #ML #HealthTech #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics

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Machine Learning with Python
In Python, image processing unlocks powerful capabilities for computer vision, data augmentation, and automationβ€”master these techniques to excel in ML engineering interviews and real-world applications! πŸ–Ό  

# PIL/Pillow Basics - The essential image library
from PIL import Image

# Open and display image
img = Image.open("input.jpg")
img.show()

# Convert formats
img.save("output.png")
img.convert("L").save("grayscale.jpg")  # RGB to grayscale

# Basic transformations
img.rotate(90).save("rotated.jpg")
img.resize((300, 300)).save("resized.jpg")
img.transpose(Image.FLIP_LEFT_RIGHT).save("mirrored.jpg")


more explain: https://hackmd.io/@husseinsheikho/imageprocessing

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Machine Learning with Python
Forwarded from Machine Learning
πŸ‘£ Rust Interview Deep Dive πŸ¦€πŸ”

A repository for systematic preparation for Rust interviews at the middle, senior, and staff levels. πŸ’ΌπŸ“š

Inside 100 real questions from interviews in product and infrastructure companies, detailed analyses with code examples and scenarios of tasks that occur in production. πŸ’»πŸ—οΈ Not "guess the program's output", but the mechanics on which real services are built. πŸ› οΈπŸš€

Here are lock-free structures, self-referential types in async, FFI with tensor libraries, correct Send on guards via await, memory ordering under loom, soundness of custom collections. πŸ”’βš‘ And it all starts with the basics. Ownership, borrowing, lifetimes. πŸ§±πŸ”„ Those who want can start from scratch or at the staff level. πŸšΆβ€β™‚οΈπŸ‘¨β€πŸ’»

https://github.com/Develp10/rustinterviewquiestions πŸ”—

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GitHub
GitHub - Develp10/rustinterviewquiestions: Rust вопорсы с собСсСдований
Rust вопорсы с собСсСдований . Contribute to Develp10/rustinterviewquiestions development by creating an account on GitHub.
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Machine Learning with Python
The guide Path to Senior Engineer Handbook has gathered resources for developers who want to advance to the level of Senior Engineer. πŸš€

Inside: πŸ“š

More than 50 newsletters on professional growth, system design, leadership, and web development. πŸ“ˆ

A selection of books on communication, technical writing, and building working relationships. 🀝

Selected YouTube channels, podcasts, and professional communities. 🎧

Courses, scientific articles, and educational platforms for a deeper study of topics. πŸŽ“

A good starting point for those who want to improve not only their technical skills, but also their architectural thinking, communication, and leadership competencies. πŸ’‘

Link: https://github.com/jordan-cutler/path-to-senior-engineer-handbook?utm_source=opensourceprojects.dev&ref=opensourceprojects.dev

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GitHub
GitHub - jordan-cutler/path-to-senior-engineer-handbook: All the resources you need to get to Senior Engineer and beyond
All the resources you need to get to Senior Engineer and beyond - jordan-cutler/path-to-senior-engineer-handbook
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