✨ Google Colab | Python Tools ✨
📖 A cloud-based Jupyter Notebook environment from Google for running Python code in a browser without any local installation.
🏷️ #Python
📖 A cloud-based Jupyter Notebook environment from Google for running Python code in a browser without any local installation.
🏷️ #Python
Forwarded from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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A collection of projects with which you can master Python by creating real applications: from backends and parsers to bots, games, and automation systems.
Instead of theory — specific tasks, step-by-step tutorials, and repositories that help hone skills through practice.
https://github.com/practical-tutorials/project-based-learning?tab=readme-ov-file#python
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GitHub
GitHub - practical-tutorials/project-based-learning: Curated list of project-based tutorials
Curated list of project-based tutorials. Contribute to practical-tutorials/project-based-learning development by creating an account on GitHub.
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Forwarded from Machine Learning with Python
SVFR — a full-fledged framework for restoring faces in videos.
It can:
Essentially, the model takes old or damaged videos and makes them "as if they were shot yesterday". And it's free and open-source.
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 damageAn ideal tool if:
#python #soft #github
https://t.me/CodeProgrammer
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Forwarded from Machine Learning with Python
A huge cheat sheet for Python, Django, Plotly, Matplotlib, P.pdf
741 KB
Many topics are covered inside:
https://t.me/CodeProgrammer
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✨ Quiz: Using Data Classes in Python ✨
📖 Test your knowledge of Python data classes, namedtuple, immutability, auto-generated methods, inheritance, and slots.
🏷️ #intermediate #python
📖 Test your knowledge of Python data classes, namedtuple, immutability, auto-generated methods, inheritance, and slots.
🏷️ #intermediate #python
Forwarded from Machine Learning with Python
📱 Python enthusiasts, this is for you — 15 BEST REPOSITORIES on GitHub for learning Python
▶️ Awesome Python — https://github.com/vinta/awesome-python
— the largest and most authoritative collection of frameworks, libraries, and resources for Python — a must-save
▶️ TheAlgorithms/Python — https://github.com/TheAlgorithms/Python
— a huge collection of algorithms and data structures written in Python
▶️ Project-Based-Learning — https://github.com/practical-tutorials/project-based-learning
— learning Python (and not only) through real projects
▶️ Real Python Guide — https://github.com/realpython/python-guide
— a high-quality guide to the Python ecosystem, tools, and best practices
▶️ Materials from Real Python — https://github.com/realpython/materials
— a collection of code and projects for Real Python articles and courses
▶️ Learn Python — https://github.com/trekhleb/learn-python
— a reference with explanations, examples, and exercises
▶️ Learn Python 3 — https://github.com/jerry-git/learn-python3
— a convenient guide to modern Python 3 with tasks
▶️ Python Reference — https://github.com/rasbt/python_reference
— cheat sheets, scripts, and useful tips from one of the most respected Python authors
▶️ 30-Days-Of-Python — https://github.com/Asabeneh/30-Days-Of-Python
— a 30-day challenge: from syntax to more complex topics
▶️ Python Programming Exercises — https://github.com/zhiwehu/Python-programming-exercises
— 100+ Python tasks with answers
▶️ Coding Problems — https://github.com/MTrajK/coding-problems
— tasks on algorithms and data structures, including for preparation for interviews
▶️ Projects — https://github.com/karan/Projects
— a list of ideas for pet projects (not just Python). Great for practice
▶️ 100-Days-Of-ML-Code — https://github.com/Avik-Jain/100-Days-Of-ML-Code
— machine learning in Python in the format of a challenge
▶️ 30-Seconds-of-Python — https://github.com/30-seconds/30-seconds-of-python
— useful snippets and tricks for everyday tasks
▶️ Geekcomputers/Python — https://github.com/geekcomputers/Python
— various scripts: from working with the network to automation tasks
React ♥️ for more posts like this💛
▶️ Awesome Python — https://github.com/vinta/awesome-python
— the largest and most authoritative collection of frameworks, libraries, and resources for Python — a must-save
▶️ TheAlgorithms/Python — https://github.com/TheAlgorithms/Python
— a huge collection of algorithms and data structures written in Python
▶️ Project-Based-Learning — https://github.com/practical-tutorials/project-based-learning
— learning Python (and not only) through real projects
▶️ Real Python Guide — https://github.com/realpython/python-guide
— a high-quality guide to the Python ecosystem, tools, and best practices
▶️ Materials from Real Python — https://github.com/realpython/materials
— a collection of code and projects for Real Python articles and courses
▶️ Learn Python — https://github.com/trekhleb/learn-python
— a reference with explanations, examples, and exercises
▶️ Learn Python 3 — https://github.com/jerry-git/learn-python3
— a convenient guide to modern Python 3 with tasks
▶️ Python Reference — https://github.com/rasbt/python_reference
— cheat sheets, scripts, and useful tips from one of the most respected Python authors
▶️ 30-Days-Of-Python — https://github.com/Asabeneh/30-Days-Of-Python
— a 30-day challenge: from syntax to more complex topics
▶️ Python Programming Exercises — https://github.com/zhiwehu/Python-programming-exercises
— 100+ Python tasks with answers
▶️ Coding Problems — https://github.com/MTrajK/coding-problems
— tasks on algorithms and data structures, including for preparation for interviews
▶️ Projects — https://github.com/karan/Projects
— a list of ideas for pet projects (not just Python). Great for practice
▶️ 100-Days-Of-ML-Code — https://github.com/Avik-Jain/100-Days-Of-ML-Code
— machine learning in Python in the format of a challenge
▶️ 30-Seconds-of-Python — https://github.com/30-seconds/30-seconds-of-python
— useful snippets and tricks for everyday tasks
▶️ Geekcomputers/Python — https://github.com/geekcomputers/Python
— various scripts: from working with the network to automation tasks
React ♥️ for more posts like this
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This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
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✨ Quiz: Interacting With REST APIs and Python ✨
📖 Test your Python REST API knowledge: consuming, building, HTTP methods, status codes, Flask, FastAPI, and Django basics.
🏷️ #intermediate #api #web-dev
📖 Test your Python REST API knowledge: consuming, building, HTTP methods, status codes, Flask, FastAPI, and Django basics.
🏷️ #intermediate #api #web-dev
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✨ code | Python Standard Library ✨
📖 Provides classes and functions for implementing read-eval-print loops and embedding interactive interpreter consoles in applications.
🏷️ #Python
📖 Provides classes and functions for implementing read-eval-print loops and embedding interactive interpreter consoles in applications.
🏷️ #Python
✨ Quiz: Using Jupyter Notebooks ✨
📖 Test your Jupyter Notebook skills: cells, modes, shortcuts, Markdown, server tools, and exporting notebooks to HTML.
🏷️ #intermediate #tools
📖 Test your Jupyter Notebook skills: cells, modes, shortcuts, Markdown, server tools, and exporting notebooks to HTML.
🏷️ #intermediate #tools
✨ codecs | Python Standard Library ✨
📖 Defines base classes for standard codecs and provides access to the codec registry for encoding and decoding text and binary data.
🏷️ #Python
📖 Defines base classes for standard codecs and provides access to the codec registry for encoding and decoding text and binary data.
🏷️ #Python
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✨ Quiz: Test-Driven Development With pytest ✨
📖 Test your TDD skills with pytest. Practice writing unit tests, following pytest conventions, and measuring code coverage.
🏷️ #intermediate #testing
📖 Test your TDD skills with pytest. Practice writing unit tests, following pytest conventions, and measuring code coverage.
🏷️ #intermediate #testing
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Forwarded from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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Forwarded from Free Online Courses
📚 Python Interview Basics for Beginners
#Development #Python #Free #Udemy
📝 prepare for next python interview
⏱ Duration: 39 m
👥 Enrollments: 23
⭐ Rating: 4 (1 reviews)
🎓 Features: Udemy • English • Beginner • Development,Python
━━━━━━━━━━━━━━━━━━━━
📢 Join our channel: @Courses27
⚠️ Note: You may need to watch a short ad to access the course. This helps keep the service free for everyone. 🙏
#Development #Python #Free #Udemy
📝 prepare for next python interview
⏱ Duration: 39 m
👥 Enrollments: 23
⭐ Rating: 4 (1 reviews)
🎓 Features: Udemy • English • Beginner • Development,Python
━━━━━━━━━━━━━━━━━━━━
📢 Join our channel: @Courses27
⚠️ Note: You may need to watch a short ad to access the course. This helps keep the service free for everyone. 🙏
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