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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Top 140 PyTorch Interview Questions and Answers

This comprehensive guide covers essential PyTorch interview questions across multiple categories, with detailed explanations for each.these 140 carefully curated questions represent the most important concepts you'll encounter in #PyTorch interviews.

๐Ÿง  Link: https://hackmd.io/@husseinsheikho/pytorch-interview

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PyTorch 2.9 has been released, an update focused on performance, portability, and developer convenience.

The fresh version brings a stable libtorch ABI for C++/CUDA extensions, symmetric memory for multi-GPU kernels, extended wheel package support for ROCm, XPU, and #CUDA 13, as well as improvements for Intel, Arm, and x86 platforms.

The release includes 3216 commits from 452 contributors, and #PyTorch 2.9 continues to develop the open source #AI ecosystem worldwide.

Full analysis: https://hubs.la/Q03NNKqW0

๐Ÿ‘‰ @codeprogrammer
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Forwarded from Github Top Repositories
๐Ÿ”ฅ Trending Repository: best-of-ml-python

๐Ÿ“ Description: ๐Ÿ† A ranked list of awesome machine learning Python libraries. Updated weekly.

๐Ÿ”— Repository URL: https://github.com/lukasmasuch/best-of-ml-python

๐ŸŒ Website: https://ml-python.best-of.org

๐Ÿ“– Readme: https://github.com/lukasmasuch/best-of-ml-python#readme

๐Ÿ“Š Statistics:
๐ŸŒŸ Stars: 22.3K stars
๐Ÿ‘€ Watchers: 444
๐Ÿด Forks: 3K forks

๐Ÿ’ป Programming Languages: Not available

๐Ÿท๏ธ Related Topics:
#python #nlp #data_science #machine_learning #deep_learning #tensorflow #scikit_learn #keras #ml #data_visualization #pytorch #transformer #data_analysis #gpt #automl #jax #data_visualizations #gpt_3 #chatgpt


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๐Ÿง  By: https://xn--r1a.website/DataScienceM
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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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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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Data Science Roadmap.pdf
15.5 MB
๐Ÿท Comprehensive Data Science Roadmap Notes

โœ… This roadmap is exactly the secret recipe you need to get out of confusion and know how to step-by-step prepare yourself for the job market.

๐Ÿ•ก From mastering Python and SQL to cleaning data and working with cloud tools, which are prerequisites for any project.

๐Ÿ•‘ How to extract real analysis reports and strategies from raw data using statistics and visualization tools.

๐Ÿ•— You will learn everything from machine learning and advanced algorithms to precise model evaluation.

๐Ÿ•™ Get familiar with neural networks, generative artificial intelligence, and language models to have a voice in today's modern world.

๐Ÿ•ง How to build real projects and portfolios that are exactly what hiring managers and big companies are looking for.

๐ŸŒ #DataScience #DataScience #pytorch #python #Roadmap

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ML Engineer, LLM Engineer, take note: TorchCode

A platform with practice tasks for basic implementations in PyTorch and questions on Transformer, which are often encountered in interviews.

โ†’ Gathers in 39 structured tasks typical for #ML #interviews - implementations of operators, modules, and architectures in #PyTorch.
โ†’ Provides auto-checking, gradient checking, time measurement, and instant feedback, so that the practice more closely resembles #LeetCode for interviews.
โ†’ Built on the basis of Jupyter Notebook, while supporting one-click reset, hints, reference solutions, and progress tracking.
โ†’ Covers such frequent topics as ReLU, Softmax, LayerNorm, Attention, RoPE, Flash Attention, #LoRA, $MoE, and others.
โ†’ Supports online mode via Hugging Face Spaces, opening individual tasks in #Google #Colab, and local launch via #Docker.

๐Ÿ‘‰ https://github.com/duoan/TorchCode
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๐Ÿ“ฑ TorchCode โ€” a PyTorch training tool for preparing for ML interviews

40 tasks for implementing operators and architectures that are actually asked in interviews. Automatic checking, hints, and reference solutions โ€” all in the browser without installation.

If you're preparing for an ML interview, it's useful to go through at least half of them.

Link: https://github.com/duoan/TorchCode

tags: #useful #pytorch

https://xn--r1a.website/CodeProgrammer โœ…
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๐ŸŽ“ A Free AI Course for Beginners by Microsoft

For those just getting into artificial intelligence, Microsoft offers a free course.

It runs for 12 weeks and includes 24 lessons with theory, hands-on assignments, labs, and quizzes.

The curriculum covers neural networks and deep learning, computer vision, natural language processing, genetic algorithms, and AI ethics. For practice, it uses the two main ML frameworksโ€”TensorFlow and PyTorch.

Each lesson follows the same structure: first, reading material, then a Jupyter notebook with code, and for some topics, a lab. The course is in English but has been translated into dozens of languages.

โžก๏ธ All materials and links are on GitHub
https://github.com/microsoft/AI-For-Beginners/blob/main/translations/ru/README.md

What's your AI level right now?

โค๏ธ โ€” Advanced user
๐Ÿ”ฅ โ€” Almost zero

#AICourse #Microsoft #DeepLearning #TensorFlow #PyTorch #MachineLearning

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