Tag: clustering

DataCamp – Unsupervised Learning in Python


From DataCamp: “Say you have a collection of customers with a variety of characteristics such as age, location, and financial history, and you wish to discover patterns and sort them into clusters. Or perhaps you have a set of texts, such as wikipedia pages, and you wish to segment them into categories based on their content. This is the world of unsupervised learning, called as such because you are not guiding, … Continue Reading

DataCamp – Unsupervised Learning in R


From DataCamp: “Many times in machine learning, the goal is to find patterns in data without trying to make predictions. This is called unsupervised learning. One common use case of unsupervised learning is grouping consumers based on demographics and purchasing history to deploy targeted marketing campaigns. Another example is wanting to describe the unmeasured factors that most influence crime differences between cities. This course provides a basic introduction to clustering and … Continue Reading



From csv,conf,v3: “csv,conf is a non-profit community conference run by some folks who really love data and sharing knowledge. If you are as passionate about data and the application it has to society as us then you should join us in Portland! This isn’t just a conference about spreadsheets. We are curating content about advancing the art of data collaboration, from putting your data on GitHub to producing meaningful insight … Continue Reading

DataCamp – Introduction to Machine Learning


From DataCamp: “This online machine learning course is perfect for those who have a solid basis in R and statistics, but are complete beginners with machine learning. After a broad overview of the discipline’s most common techniques and applications, you’ll gain more insight into the assessment and training of different machine learning models. The rest of the course is dedicated to a first reconnaissance with three of the most basic machine … Continue Reading

IEEE International Conference on Data Mining


Next Event: November 18-21, 2017 – New Orleans, LA From ICDM: “The IEEE International Conference on Data Mining series (ICDM) has established itself as the world’s premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of data mining, including algorithms, software and systems, and applications.”

Predictive Analytics World – San Francisco


2017 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  



Next event: April 8-11, 2018 – Austin, TX Stay up-to-date for AnacondaCON 2018 From AnacondaCON: AnacondaCON is the place to fast track your current knowledge of Open Data Science, through engagement with visionaries who have established modern Open Data Science technology and are pioneering its evolution. You’ll learn best practices and how other thought leaders are leveraging Anaconda to accelerate the value from their data.   Highlights from AnacondaCON 2017 … Continue Reading

Microsoft Azure Machine Learning Cheat Sheet


The Microsoft Azure Machine Learning Algorithm Cheat Sheet helps you choose the right machine learning algorithm for your predictive analytics solutions from the Microsoft Azure Machine Learning library of algorithms.

The Analytics Edge

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Through inspiring examples and stories, discover the power of data and use analytics to provide an edge to your career and your life.

Data Smart: Using Data Science to Transform Information into Insight


Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that’s done within the familiar environment of a spreadsheet.