Name: George Mount
Type: User
Company: Stringfest Analytics
Bio: Founder, @stringfestdata; Author, Advancing into Analytics: From Excel to Python and R (@OReillyMedia, 2021); @Microsoft Excel MVP
Twitter: gjmount
Location: Cleveland, OH, USA
Blog: stringfestanalytics.com
George Mount's Projects
For the book Learn Data Mining through Excel
Jumpstart your integration of the Learnosity APIs into your learning platform.
Data Dashboards with R and Shiny
Objective: Students can formulate a research question, conduct preliminary data analysis, and prepare data, and select features, build, evaluate, optimize a model using regression
How to mail merge from Excel to Word with a Table of Contents
Microsoft Power BI Cookbook, published by Packt
Repo for LiveProject on ML feature engineering in Python
12 weeks, 25 lessons, 50 quizzes, classic Machine Learning for all
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
Code for NLTK3 Cookbook
Employee database featuring the cast of The Office
Resources for O'Reilly Online Learning course, "Advanced Excel Statistics for Business Analytics"
Resources for O'Reilly Online Learning course, "First Steps with Power Query for Microsoft Excel"
Resources for O'Reilly OLT session, "R-Powered Excel for Business Analytics"
Pandas Cookbook Second Edition, published by Packt
Complete source code (datasets and Jupyter Notebooks) for Pandas In Action
Code and Data for the book "Practical SQL" by Anthony DeBarros, published by No Starch Press (2018).
Code repository for O'Reilly book
Applied Probability Theory for Everyone
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
Repository for the Python & R for the Modern Data Scientists Book
Companion code repository for the O'Reilly "Python and R for the Modern Data Scientist" book.
This is an example of how to use Python and Jupyter Notebook to explore a given dataset.
This is the companion repo of the O'Reilly book "Python for Excel".
This repository collects all interesting Python one-liners. Feel free to submit yours!