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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🔥 A huge collection of the 17 best GitHub repositories for learning Python.

Perfect for those who want to level up from print('Hello') to advanced projects.


😰 Let's go:
1. 30-Days-Of-Python — a 30-day Python challenge covering the basics of the language.

2. Python Basics — simple and clear Python basics for beginners.

3. Learn Python — a topic-based guide with examples and code.

4. Python Guide — best practices, tools, and advanced topics.

5. Learn Python 3 — an easy-to-understand guide to Python 3 with practice.

6. Python Programming Exercises — 100+ Python exercises.

7. Coding Problems — algorithmic problems, perfect for interview prep.

8. Project-Based-Learning — learn Python through real projects.

9. Projects — ideas for practical projects and skill improvement.

10. 100-Days-Of-ML-Code — a step-by-step guide to Machine Learning in Python.

11. TheAlgorithms/Python — a huge collection of algorithms in Python.

12. Amazing-Python-Scripts — useful scripts from automation to advanced utilities.

13. Geekcomputers/Python — a collection of practical scripts: networking, files, automation.

14. Materials — code, exercises, and projects from Real Python.

15. Awesome Python — a top list of the best frameworks and libraries.

16. 30-Seconds-of-Python — short snippets for quick solutions.

17. Python Reference — life hacks, tutorials, and useful scripts.

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#python #doc #github #soft
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⚡️ Colorizing old black-and-white videos and "bringing faces to life" for FREE

SVFR — a full-fledged framework for restoring faces in videos.

It can:
💬 BFR — improve blurry faces.
💬 Colorization — colorize black-and-white videos.
💬 Inpainting — redraw damaged areas.
💬 and combine all of this in one pass.

Essentially, the model takes old or damaged videos and makes them "as if they were shot yesterday". And it's free and open-source.

⚙️ Installation locally:

1. Create an environment

conda create -n svfr python=3.9 -y
conda activate svfr


2. Install PyTorch (for your CUDA)

pip install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2


3. Install dependencies

pip install -r requirements.txt


4. Download models

conda install git-lfs
git lfs install
git clone https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt models/stable-video-diffusion-img2vid-xt


5. Start processing videos

python infer.py \
--config config/infer.yaml \
--task_ids 0 \
--input_path input.mp4 \
--output_dir results/ \
--crop_face_region


Where task_ids:

* 0 — face enhancement
* 1 — colorization
* 2 — redrawing damage

An ideal tool if:
🟢you're restoring archival videos;
🟢you're creating historical content;
🟢you're working with neural networks and video effects;
🟢you want a wow result without paid services.

▶️ Demo on Hugging Face

♎️ GitHub/Instructions

#python #soft #github

https://t.me/CodeProgrammer
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