How to remove jupyter notebook metadata/output before tracking with git?
There are several method including git filter approuch, git hooks and using
it lunches each time ADD changes of the notebook.
There are several method including git filter approuch, git hooks and using
nbstripout
. I use the filter since looked cleaner to me.bashto remove the output change
# Add this to your local .git/config
[filter "strip-notebook-output"]
clean = "jupyter nbconvert --ClearOutputPreprocessor.enabled=False --ClearMetadataPreprocessor.enabled=True --to=notebook --stdin --stdout --log-level=ERROR"
# Create a .gitattributes file in your directory with notebooks, with this content:
*.ipynb filter=strip-notebook-output
--ClearOutputPreprocessor.enabled=True.
it lunches each time ADD changes of the notebook.
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Scientific Programming
How to remove jupyter notebook metadata/output before tracking with git? There are several method including git filter approuch, git hooks and using nbstripout. I use the filter since looked cleaner to me. bash # Add this to your local .git/config [filterβ¦
YouTube
nbstripout: strip output from Jupyter and IPython notebooks
This screencast demonstrates the use and working principles behind the nbstripout utility and how to use it as a Git filter
Forwarded from Microsoft Copilot
You are invited to Microsoft Copilot AI assistant!
Copilot is your one-stop destination within Telegram for answers, advice, and fun conversations.β¨
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Copilot is your one-stop destination within Telegram for answers, advice, and fun conversations.β¨
Click on this link to start: Chat with Copilot
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Lazy Predict Library in Python for Machine Learning
Lazy Predict is a Python library designed to simplify and accelerate predictive modeling projects. It offers a user-friendly, efficient approach to making predictions, requiring minimal effort to install and use. This open-source tool, released under the MIT license, is ideal for data science and machine learning tasks.
Key benefits of Lazy Predict include its ability to streamline data pre-processing, model tuning, and result evaluation. It also provides features for model selection and hyperparameter optimization, helping users achieve better outcomes with their machine learning models. By leveraging Lazy Predict, you can enhance your predictive modeling process and achieve more accurate results efficiently.
GeeksforGeeks
GitHub
Lazy Predict is a Python library designed to simplify and accelerate predictive modeling projects. It offers a user-friendly, efficient approach to making predictions, requiring minimal effort to install and use. This open-source tool, released under the MIT license, is ideal for data science and machine learning tasks.
Key benefits of Lazy Predict include its ability to streamline data pre-processing, model tuning, and result evaluation. It also provides features for model selection and hyperparameter optimization, helping users achieve better outcomes with their machine learning models. By leveraging Lazy Predict, you can enhance your predictive modeling process and achieve more accurate results efficiently.
GeeksforGeeks
GitHub
GeeksforGeeks
Lazy Predict Library in Python for Machine Learning - GeeksforGeeks
Your All-in-One Learning Portal: GeeksforGeeks is a comprehensive educational platform that empowers learners across domains-spanning computer science and programming, school education, upskilling, commerce, software tools, competitive exams, and more.
Perplexity has added a nice feature of attaching PDF and ask from it. Just upload your pdf through (+) and ask question.
Scientific Programming
Perplexity has added a nice feature of attaching PDF and ask from it. Just upload your pdf through (+) and ask question.
If you need more complete option, there is also this repository to make a chatbot using LangChain (haven't tried that personally) and train using multiple pdf/books.
GitHub
GitHub
GitHub
GitHub - sabber-slt/pdfai: PDF based Chatbot using streamlit LangChain & OpenAI.
PDF based Chatbot using streamlit LangChain & OpenAI. - sabber-slt/pdfai
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How to download part of a GitHub repository? for example one folder.
Sometimes a Repository could be very large and you only need part of it.
1. Go to https://download-directory.github.io/
2. Enter the URL of the GitHub repository folder you want to download in the input field.
3. Press Enter, and the folder will be downloaded as a ZIP file.
There are also other methods using git command or GitHub Desktop, but this one seems easier.
Sometimes a Repository could be very large and you only need part of it.
1. Go to https://download-directory.github.io/
2. Enter the URL of the GitHub repository folder you want to download in the input field.
3. Press Enter, and the folder will be downloaded as a ZIP file.
There are also other methods using git command or GitHub Desktop, but this one seems easier.
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Have you heard about the Qajar image collection? Iβve prepared a notebook to add color to these precious pictures.
notebook: https://drive.google.com/file/d/1rfvp-1lKBwA675A6c0isV8ig2T8EtbNe/view?usp=sharing
It will be run on colab, just need to upload image on your colab and colorize them.
Images: https://drive.google.com/drive/folders/1XVE6EGD8kYnR2G8rR_Dc0JKYi9ykA0vg
notebook: https://drive.google.com/file/d/1rfvp-1lKBwA675A6c0isV8ig2T8EtbNe/view?usp=sharing
It will be run on colab, just need to upload image on your colab and colorize them.
Images: https://drive.google.com/drive/folders/1XVE6EGD8kYnR2G8rR_Dc0JKYi9ykA0vg
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Here are the Colored images:
https://t.me/QajarC
https://t.me/QajarC
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High-Performance Computing with Python @ JSC
The following topics will be covered:
Short review of vectorized programming with NumPy
Interactive parallel programming with IPython
Profiling and optimization
High-performance NumPy
Just-in-time compilation with numba
Distributed-memory parallel programming with Python and MPI
Bindings to other programming languages and HPC libraries
Interfaces to GPUs
https://gitlab.jsc.fz-juelich.de/sdlbio-courses/hpc-python-2024
The following topics will be covered:
Short review of vectorized programming with NumPy
Interactive parallel programming with IPython
Profiling and optimization
High-performance NumPy
Just-in-time compilation with numba
Distributed-memory parallel programming with Python and MPI
Bindings to other programming languages and HPC libraries
Interfaces to GPUs
https://gitlab.jsc.fz-juelich.de/sdlbio-courses/hpc-python-2024
GitLab
sdlbio-courses / HPC Python 2024 Β· GitLab
GitLab - JSC
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