Data Mining


Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)
Introduction to Data Mining
Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
Data Mining: Introductory and Advanced Topics
Programming Collective Intelligence: Building Smart Web 2.0 Applications
Mining of Massive Datasets
Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart
Doing Data Science: Straight Talk from the Frontline
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with Xlminer
Python for Data Analysis
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
Data Mining with Microsoft SQL Server 2008
AI Doctor by Ronald M. RazmiPattern Recognition and Machine Learning by Christopher M. BishopUnmasking AI by Joy BuolamwiniThe Coming Wave by Mustafa SuleymanThe Elements of Statistical Learning by Trevor Hastie
Machine Learning
102 books — 112 voters
Machine Learning by Samuel HackMachine Learning Mathematics by Samuel HackThe Text Mining Handbook by Ronen FeldmanDoing Corpus Linguistics by William J. CrawfordWord by Word by Kory Stamper
Data Mining and Writing (nonfiction)
25 books — 3 voters

AI Doctor by Ronald M. RazmiDeep Utopia by Nick BostromCo-Intelligence by Ethan MollickSuperintelligence by Nick BostromUnmasking AI by Joy Buolamwini
Best machine learning books
86 books — 78 voters

Perhaps its time to dumb down our “smart” life. We are being tracked, listened to, data mined, recorded, and so much more without our real knowing or understanding. When are we going to make a stand for our right to privacy? That’s Tremendo Bullship!
Rosangel Perez

Kent Stern
You should be able to reconcile past events in a matter of seconds. However, if you do not know what is or has happened, you must take an offensive posture and actively seek out those agents and transactions based on multiple dimensions over time. This is the environment in which you will work and you must build a security model that can actively detect, monitor and pursue that activity.
Kent Stern, Obtaining Actionable Intelligence for CINDER Threat Detection using DMX Mining Models

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Includes data mining, data visualization, machine learning and many other question related to
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Datacool Readers Group Grupo de lectores de libros sobre datos
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