jeremy886 / learn_datascience

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End-to-End Data Science Workflows in Jupyter Notebooks #8

Closed jeremy886 closed 6 years ago

jeremy886 commented 6 years ago

SafariOnline 2018-02-01

Project Jupyter & the Jupyter Ecosystem [30 min]

“Human in the loop computing”; facilitating collaboration and sharing in data science
Jupyter’s history and roots in IPython and IPython Notebooks
Jupyter & NumFOCUS
Finding Resources on Jupyter.org
Installation
Documentation
Community
Hosted notebooks: nbviewer / GitHub
Gallery of Interesting Jupyter Notebooks
Current Development Work
JupyterHub
JupyterLab
Widgets
Real Time Collaboration
Contributing to the Jupyter ecosystem via GitHub & enhancement proposals

Notebook [30 min]

Installing the Anaconda Distribution of Python
Navigating the Jupyter Notebook
Quantitative and visual exploratory data analysis in Python
Connecting to datasets
Data Visualization packages: matplotlib, seaborn, plotly, Bokeh, Altair

BREAK

Kernels [15 min]

Which Python?
Language-specific notebooks
Installing the R kernel
Installing other data science kernels: Scala, Julia

nbconvert [30 min]

Converting your Jupyter Notebook to a slide presentation or html document

BREAK

Sharing notebooks [30 min]

Working with .ipynb files
Using Jupyter using the command line
nteract
Azure notebooks
Using Anaconda console
try.jupyter.org

nbdime for diffing notebooks [20 min]

Learn more about other projects in the ecosystem [25 min]

JupyterHub
JupyterLab
Widgets
Real Time Collaboration