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altair-tutorial

Notebooks for the Altair tutorial

assets

baseline-rs

python implementation baseline recommender systems

beautiful_objects

Content from "Making Beautiful Objects with Jupyter", originally presented at JupyterCon2018

blobster

A convenient way to manage your Azure Data Storage with Python.

blog

certificates

code-snippets

Python and R code snippets

code-vault

Collection of useful notebooks and snippets

datacamp-python-data-science-track

All the slides, accompanying code and exercises all stored in this repo. 🎈

datasets

some toy datasets to play with

dbda-python

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

deep-learning-for-time-series-data-cookbook

B21145 - Deep Learning for Time Series Data Cookbook

deltaframe

A convenient way to manage to show and log the delta between two Pandas dataframes.

dft

transform a pandas dataframe in a convenient way using a pipeline approach

diff-means-half-dozen-ways

Run standard t-tests, simulations, and Bayesian difference in means tests with R and Stan

dproc

A convenient way to preprocess your data by using metadata.

eda_examples

examples of exploratory data analysis

eventchain

Building event chains in a convenient way

hands-on-data-analysis-with-pandas

Materials for following along with Hands-On Data Analysis with Pandas.

hands-on-recommendation-systems-with-python

Hands-On Recommendation Systems with Python published by Packt

islr-python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

kmeans_from_scratch

machine-learning-mindmap

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

markdown-here

Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.

matplotlib-gallery

Examples of matplotlib codes and plots

mlwpy_code

Code from the Pearson Addison-Wesley book Machine Learning with Python for Everyone

nycdsa_project_5_recommender

Python

pycon-2017-eda-tutorial

Resources for the PyCon 2017 tutorial, "Exploratory data analysis in python"

r-for-everyone-code-samples

Code Examples used in https://www.amazon.com/Everyone-Advanced-Analytics-Graphics-Addison-Wesley/dp/013454692X