Data Analytics


Storytelling with Data: A Data Visualization Guide for Business Professionals
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
Lean Analytics: Use Data to Build a Better Startup Faster
The Art of Statistics: How to Learn from Data
Python for Data Analysis
Naked Statistics: Stripping the Dread from the Data
The Signal and the Noise: Why So Many Predictions Fail—But Some Don't
Invisible Women: Data Bias in a World Designed for Men
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
Data Analytics Made Accessible
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
The Visual Display of Quantitative Information
Visualize This: The FlowingData Guide to Design, Visualization, and Statistics
A Guide To Inbound Marketing For Small Business by Izabela CottleThe Future of Artificial Intelligence in Digital Marketing by Maria JohnsenSales in The Age Of Intelligent Web by Maria JohnsenBlockchain in Digital Marketing-A New Paradigm of Trust by Maria JohnsenMultilingual Digital Marketing by Maria Johnsen
Digital Marketer Books
42 books — 14 voters

The Signal and the Noise by Nate SilverThe Elements of Statistical Learning by Trevor HastieMoneyball by Michael   LewisThe Visual Display of Quantitative Information by Edward R. TufteAn Introduction to Statistical Learning by Gareth James
Data Science - Learning About Data
133 books — 121 voters

My brief exposure to hacking communities left a permanent impression. You learn that no system is absolutely –nothing is impenetrable and barriers are a dare. The hacker philosophy taught me that if you shift your perspective on any system: a computer, a network, even society, you may discover flaws and vulnerabilities.
Christopher Wylie, Mindf*ck: Cambridge Analytica and the Plot to Break America

Using this technique, Baum et al constructed a forest that contained 1,000 decision trees and looked at 84 co-variates that may have been influencing patients' response or lack of response to the intensive lifestyle modifications program. These variables included a family history of diabetes, muscle cramps in legs and feet, a history of emphysema, kidney disease, amputation, dry skin, loud snoring, marital status, social functioning, hemoglobin A1c, self-reported health, and numerous other chara ...more
Paul Cerrato, Reinventing Clinical Decision Support: Data Analytics, Artificial Intelligence, and Diagnostic Reasoning

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#DS4HS A group for the data friendly and those who want to be
1 member, last active 7 years ago
This is a group for students of the MS in Analytics Gatech program. This space is for sharing an…more
1 member, last active 8 years ago
Kick off this new year with a thrilling reading challenge
2 members, last active one year ago
Datacool Readers Group Grupo de lectores de libros sobre datos
12 members, last active 2 years ago