uberwach / leveling-up-jupyterLinks
Leveling up your Jupyter notebook skills
☆79Updated 8 years ago
Alternatives and similar repositories for leveling-up-jupyter
Users that are interested in leveling-up-jupyter are comparing it to the libraries listed below
Sorting:
- Reproducible Data Analysis Workflow in Jupyter☆118Updated 7 years ago
- Materials for PyCon 2017 presentation on optimizing Pandas code☆213Updated 6 years ago
- Using Project Jupyter for data science.☆258Updated 4 years ago
- Scipy 2017 scikit-learn tutorial by Alex Gramfort and Andreas Mueller☆288Updated 8 years ago
- Materials for the "Advanced Scikit-learn" class in the afternoon☆165Updated 7 years ago
- 📈 Interactive comparison of Python plotting libraries for exploratory data analysis. Examples of using Pandas plotting, plotnine, Seabor…☆112Updated last month
- Example Python DS project☆71Updated 7 years ago
- PyData NYC 2017: Pandas Head to Tail☆57Updated 8 years ago
- Materials for the pandas tutorial at PyData Chicago 2016☆56Updated 5 years ago
- code for my "stupid itertools tricks" talk from pydata seattle 2015☆153Updated 9 years ago
- Code for my OSCON 2015 talk☆83Updated 10 years ago
- Scikit-Learn Tutorial for PyData Seattle 2015☆136Updated 10 years ago
- Building Python Data Applications with Blaze and Bokeh Tutorial, SciPy 2015☆144Updated 10 years ago
- Code for a workshop on statistical interference using computational methods in Python.☆226Updated 4 years ago
- A Jupyter notebook to accompany Jake VanderPlas's "Statistics for Hackers" talk from PyCon 2016.☆77Updated 7 years ago
- ☆41Updated 9 years ago
- Material for Talk at PyData Seattle 2017☆168Updated 7 years ago
- ☆317Updated 4 years ago
- Tutorials on visualizing data using python packages like bokeh, plotly, seaborn and igraph☆270Updated 5 years ago
- ☆195Updated 6 months ago
- ☆136Updated 6 years ago
- Machine learning with scikit-learn tutorial at PyData Chicago 2016☆128Updated 9 years ago
- COMS W4995 Applied Machine Learning - Spring 18☆157Updated 6 years ago
- Code material for a data science tutorial☆197Updated 8 years ago
- A short tutorial for data scientists on how to write tests for code + data.☆121Updated 5 years ago
- For the pandas tutorial at PyData Seattle: https://www.youtube.com/watch?v=otCriSKVV_8☆116Updated 4 years ago
- Jupyter notebooks from my O'Reilly Media course "Matplolib for Developers: Data Visualization and Analysis with Python"☆140Updated 8 years ago
- Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller☆249Updated 7 years ago
- An introduction to implementing a number of scikit-learn classifiers, along with some data exploration☆102Updated 9 years ago
- Jupyter notebook presentations with optional code visibility and no ugly elements☆68Updated 8 years ago