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Sales forecasting using Machine Learning
SpringML inviting business and sales leaders to its Man vs Machine Forecasting Duel - give them a day with your data and they will provide an algorithm based, unbiased forecast.
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 Cartoon: Machine Learning – What They Think I Do
Different views of Machine Learning: What society, my friends, my parents, other programmers think I do, and what I really do.
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Dataiku: The Complete Data Sheet
Whether your every day tool is Scala, Python, R, or Excel, you can now use one tool - Dataiku - to transform raw data to predictions without the hassle. Discover the platform!
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E-learning courses on Advanced Analytics, Credit Risk Modeling, and Fraud Analytics
These online courses, developed by Prof. Bart Baesens and SAS, include videos, case studies, quizzes, and focus on focusses on the concepts and modeling methodologies and not on specific software.
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Introduction to Anomaly Detection
This overview will cover several methods of detecting anomalies, as well as how to build a detector in Python using simple moving average (SMA) or low-pass filter.
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PLOTCON, Largest Data Visualization Event of its kind, Oakland, May 2-5
For data scientists, journalists, and business analysts, PLOTCON is THE opportunity to meet the creators of the tools you use everyday, ask questions, hear where the future is heading, and be part of the conversation. Use code KDNUGGETS to save.
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Getting Up Close and Personal with Algorithms
We've put together a brief summary of the top algorithms used in predictive analysis, which you can see just below. Read to learn more about Linear Regression, Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, and more.
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The Challenges of Building a Predictive Churn Model
Unlike other data science problems, there is no one method for predicting which customers are likely to churn in the next month. Here we review the most popular approaches.
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What is Customer Churn Modeling? Why is it valuable?
Getting new customers is much more more expensive than retaining existing ones, so reducing churn is a top priority for many firms. Understanding why customers churn and estimating the risks are powerful components of a data-driven retention strategy.
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Introduction to Correlation
Correlation is one of the most widely used (and widely misunderstood) statistical concepts. We provide the definitions and intuition behind several types of correlation and illustrate how to calculate correlation using the Python pandas library.
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Cartoon: Machine Learning – What They Think I Do
Getting Up Close and Personal with Algorithms