Subject
14 entries
Jupyter
Bookmarks
Activation Steering Notebook (concentration_notebooks)
A Jupyter notebook exploring activation steering in neural networks from the concentration_notebooks repo. Saved as a reference in the mechanistic interpretability and model steering space.
pygwalker: Pandas DataFrame to Tableau-Style UI
pygwalker turns a pandas DataFrame into a drag-and-drop Tableau-style visual analysis interface inside Jupyter notebooks — one line of code to replace writing matplotlib/seaborn boilerplate with interactive visual exploration. Strong tool for exploratory data analysis.
jupyter-text2code: English to Python in Jupyter
jupyter-text2code is a proof-of-concept Jupyter extension that converts English queries into Python code — an early 2021 demonstration of natural language to code generation in notebooks, before Copilot and ChatGPT made this mainstream.
Jupyter Notebooks Gallery — notebook.community
notebook.community is a curated gallery of publicly shared Jupyter notebooks — a discovery layer for interesting notebooks covering machine learning, data analysis, visualization, and scientific computing. Good for finding worked examples.
Data Science Meets DevOps: MLOps with Jupyter, Git, and Kubernetes
Kubeflow's blog post on MLOps practices combining Jupyter notebooks, Git, and Kubernetes — the infrastructure side of making ML reproducible, collaborative, and deployable. Establishes the canonical MLOps stack for Kubernetes-based ML teams.
Dive into Machine Learning
A curated GitHub guide for learning machine learning hands-on with Jupyter notebooks and scikit-learn — one of the most-starred beginner ML resources of 2015. Its strength is pairing interactive notebooks with curated external readings rather than building yet another tutorial from scratch.
Rodeo: A Data Science IDE for Python
yhat's 2015 launch of Rodeo — a Python IDE built for data science workflows, modeled on RStudio's four-pane layout. It didn't outlast the market consolidation around Jupyter Lab and VS Code, but its design assumptions turned out to be right.
Notebook Gallery: Best IPython Notebooks
A curated gallery of the most-viewed IPython/Jupyter notebooks — an early community resource for discovering high-quality notebook examples across ML, data analysis, and scientific computing. Predecessor to nbviewer and the current ecosystem of notebook sharing platforms.
Seaborn — Plotting Distributions Notebook
Seaborn's official distribution-plotting example notebook — demonstrates the library's statistical visualization API for histograms, KDE plots, rug plots, and joint distributions. The reference for anyone learning to visualize data distributions in Python.
Exploratory Computing with Python — Mark Bakker
Mark Bakker's open course on exploratory computing with Python — Jupyter notebooks covering NumPy, Matplotlib, and scientific computing techniques. Aimed at engineers and scientists who want to use Python for quantitative analysis without a computer science background.
IPython Notebook — msund Gist
An IPython notebook shared via gist by msund — likely conference or tutorial materials from the 2014 Python/data science community. Saved without content, context inferred from surrounding bookmarks in the same PyData period.
MH370 MCMC Notebook — Conor Myhrvold
Conor Myhrvold's IPython notebook using Monte Carlo simulation to analyze the probable flight path of MH370 from satellite pings. An early high-profile example of using Bayesian inference and simulation for real-world analysis.
My Favorite 7 IPython Notebooks
A curated list of seven standout IPython Notebooks shared in early 2014 — when the notebook format was the primary vehicle for sharing data science work and reproducible analysis. Reflects the community's excitement about executable, shareable computation.
A Gallery of Interesting IPython Notebooks
Curated GitHub wiki of interesting IPython Notebooks covering scientific computing, data analysis, machine learning, and visualization. The 2014 canonical list of notebooks worth running — before nbviewer and Binder made sharing notebooks routine.