Tag: decision trees

DataCamp – Credit Risk Modeling in R

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From DataCamp: “This hands-on-course with real-life credit data will teach you how to model credit risk by using logistic regression and decision trees in R. Modeling credit risk for both personal and company loans is of major importance for banks. The probability that a debtor will default is a key component in getting to a measure for credit risk. While introducing other models in this course as well, we focus on … Continue Reading

Predictive Analytics World – Chicago 2017

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Upcoming Event: June 19-22, 2017 – Chicago, IL Co-Located with PAW Manufacturing Conference: http://www.predictiveanalyticsworld.com/mfg/2017/ From Predictive Analytics World: Predictive Analytics World is the leading cross-vendor event for predictive analytics professionals, managers and commercial practitioners. The only conference of its kind, Predictive Analytics World delivers vendor-neutral sessions across verticals such as banking, financial services, e-commerce, entertainment, government, healthcare, manufacturing, high technology, insurance, non-profits, publishing, and retail. 2017 Speakers

Predictive Analytics World – San Francisco 2017

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Upcoming Event: May 14-18, 2017 From Predictive Analytics World: Predictive Analytics World is the leading cross-vendor event for predictive analytics professionals, managers and commercial practitioners. he only conference of its kind, Predictive Analytics World delivers vendor-neutral sessions across verticals such as banking, financial services, e-commerce, entertainment, government, healthcare, manufacturing, high technology, insurance, non-profits, publishing, and retail. Overview of PAW Conference 2017 Speakers  

Data Science for Business: What you need to know about data mining and data-analytic thinking

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Learn how to improve communication between business stakeholders and data scientists, and how to participate intelligently in your company’s data science projects. Discover how to think data-analytically, support business decision-making with data science methods.

KDNuggets Data Mining Course

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This course contains modules for a complete 1-semester course in data mining and individual lectures on data mining in the context of courses on Algorithms, Artificial Intelligence, and Introduction to Computer Science.

Data Science from Scratch: First Principles with Python

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In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.

Machine Learning: The Art and Science of Algorithms that Make Sense of Data

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With hundreds of worked examples and explanatory figures, the book explains the principles behind state-of-the-art methods for making sense of data in an intuitive yet precise manner.

Programming Collective Intelligence: Building Smart Web 2.0 Applications

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This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet.

An Introduction to Statistical Learning: with Applications in R

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Provides an accessible overview of the field of statistical learning… This book presents some of the most important modeling and prediction techniques, along with relevant applications.

Doing Data Science: Straight Talk from the Frontline

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How can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.