# Tag: Data Mining (159)

**Data Mining Book – Chapter Download**- Dec 4, 2018.

Download this immediately useful book chapter, and learn how to create derived variables, which allow the statistical and Data Science modeling to incorporate human insights.**Data Mining Book – Chapter Download**- Nov 2, 2018.

Download this immediately useful book chapter, and learn how to create derived variables, which allow the statistical and Data Science modeling to incorporate human insights.**Data Mining Book: Chapter Download.**- Oct 10, 2018.

Download this immediately useful book chapter, and learn how to create derived variables, which allow the statistical and Data Science modeling to incorporate human insights.**Data Mining Book – Chapter Download.**- Sep 7, 2018.

**What on earth is data science?**- Sep 4, 2018.

An overview and discussion around data science, covering the history behind the term, data mining, statistical inference, machine learning, data engineering and more.**Data Mining Book – Chapter Download**- Aug 7, 2018.

Download this very useful book chapter, and learn how to create derived variables, which allow the statistical and Data Science modeling to incorporate human insights.**Data Mining Book Chapter Download**- Jul 9, 2018.

Download this chapter by Gordon Linoff and Michael Berry, and learn how to create derived variables, which allow the statistical modeling process to incorporate human insights.**Every time someone runs a correlation coefficient on two time series, an angel loses their wings**- Jun 18, 2018.

We all know correlation doesn’t equal causality at this point, but when working with time series data, correlation can lead you to come to the wrong conclusion.**Madrid Advanced Statistics and Data Mining Summer School**- Mar 19, 2018.

The courses cover topics such as Neural Networks and Deep Learning, Bayesian Networks, Big Data with Apache Spark, Bayesian Inference, Text Mining and Time Series. Each course has theoretical and practical classes, the latter done with R or Python.**Stanford online Data Science, Data Mining courses and certificates**- Feb 21, 2018.

With our online graduate courses and certificates, you can earn a higher education credential from Stanford while still maintaining your career.**5 Things You Need To Know About Data Science**- Feb 19, 2018.

Here are 5 useful things to know about Data Science, including its relationship to BI, Data Mining, Predictive Analytics, and Machine Learning; Data Scientist job prospects; where to learn Data Science; and which algorithms/methods are used by Data Scientists**Apple: Data Mining Scientist**- Feb 13, 2018.

Seeking an outstanding data scientist who is interested in designing, developing, and fielding data mining solutions that have direct and measurable impact to Apple.**Umeå University: 2-Years Postdoctoral researcher position on Data Mining / Knowledge Systems**- Jan 30, 2018.

Join our efforts to build up Registry Data Federation and Analysis Research Infrastructure. Develop data analysis methods with focus of data federation and privacy preservation.**Training Sets, Test Sets, and 10-fold Cross-validation**- Jan 9, 2018.

More generally, in evaluating any data mining algorithm, if our test set is a subset of our training data the results will be optimistic and often overly optimistic. So that doesn’t seem like a great idea.**Stanford online Data Science and Data Mining courses and certificates**- Nov 10, 2017.

With our Online Data Mining Certificates, you’ll learn to guide important business decisions, become indispensable to your organization, and give your career a boost. Benefit from flexibility, world-class teaching and research, and a Stanford credential.**Process Mining with R: Introduction**- Nov 2, 2017.

In the past years, several niche tools have appeared to mine organizational business processes. In this article, we’ll show you that it is possible to get started with “process mining” using well-known data science programming languages as well.**Short course: Statistical Learning and Data Mining IV, NYC, Nov 2-3**- Oct 13, 2017.

This new two-day course gives a detailed and modern overview of statistical models used by data scientists for prediction and inference, with emphasis on tools useful for tackling modern-day data analysis problems.**Videos for Business Analytics using Data Mining course**- Sep 12, 2017.

Here we present links to very useful videos on Business Analytics using data mining courses.**Data Science Primer: Basic Concepts for Beginners**- Aug 11, 2017.

This collection of concise introductory data science tutorials cover topics including the difference between data mining and statistics, supervised vs. unsupervised learning, and the types of patterns we can mine from data.**Insights from Data mining of Airbnb Listings**- Aug 4, 2017.

AirBnB has 2 million listings and operates in 65,000 cities. Here we look at insights related to vacation rental space in the sharing economy using the property listings data for Texas, US.**IEEE ICDM 2017 Call For Award Nominations, due Aug 15**- Jul 20, 2017.

Nominations sought for outstanding research and service contributions in the field of data mining and data science.**Top 15 Python Libraries for Data Science in 2017**- Jun 13, 2017.

Since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity.**Data Mining Techniques, Free Chapter: Derived Variables – Making the Data Mean More**- Jun 12, 2017.

Download this chapter by Gordon Linoff and Michael Berry, and learn how to create derived variables, which allow the statistical modeling process to incorporate human insights.**Madrid UPM Advanced Statistics and Data Mining Summer School, June 26 – July 7**- May 12, 2017.

The courses cover topics such as Neural Networks and Deep Learning, Bayesian Networks, Big Data with Apache Spark, Bayesian Inference, Text Mining and Time Series, and each has theoretical as well as practical classes, done with R or Python. Early bird till June 5.**Stanford Online Data Mining & Data Science Courses**- May 11, 2017.

Stanford Data Mining Courses and Certificates are designed to give you the skills you need to gather and analyze massive amounts of information, and to translate that information into actionable business strategies. Enroll until June 18.**Do We Need Balanced Sampling?**- May 4, 2017.

Resampling is a solution which is very popular in dealing with class imbalance. Our research on churn prediction shows that balanced sampling is unnecessary.**SUNY Buffalo: Postdoc in Data Mining and Bioinformatics**- Apr 19, 2017.

Seeking a Postdoctoral Associate in the areas of machine learning and bioinformatics. The major research focus is on developing machine learning and mathematics methodologies for analyzing massive genomic data.**IRIS Advanced Engineering: TecnioSpring Data Mining Fellowship**- Mar 9, 2017.

Experienced researcher to carry out different data mining projects with emphasis on industrial applications. This is a 24-month fellowship targeted at persons with a Ph.D. or similar research experience.**Short course: Statistical Learning and Data Mining IV, Palo Alto, Apr 6-7**- Feb 21, 2017.

This new two-day course gives a detailed and modern overview of statistical models used by data scientists for prediction and inference, with emphasis on tools useful for tackling modern-day data analysis problems.**Boost your career with Stanford data mining courses**- Feb 14, 2017.

Be a member of an on-campus graduate class, watch lectures and complete assignments online, and digitally interact with your classmates. Stanford data mining courses: Flexibility. World-Class Teaching and Research. Stanford Credential.**Fixing Deployment and Iteration Problems in CRISP-DM**- Feb 1, 2017.

Many analytic models are not deployed effectively into production while others are not maintained or updated. Applying decision modeling and decision management technology within CRISP-DM addresses this.**Bringing Business Clarity To CRISP-DM**- Jan 24, 2017.

Many analytic projects fail to understand the business problem they are trying to solve. Correctly applying decision modeling in the Business Understanding phase of CRISP-DM brings clarity to the business problem.**The Data Science Puzzle, Revisited**- Jan 20, 2017.

The data science puzzle is re-examined through the relationship between several key concepts in the realm, and incorporates important updates and observations from the past year. The result is a modified explanatory graphic and rationale.**Four Problems in Using CRISP-DM and How To Fix Them**- Jan 18, 2017.

CRISP-DM is the leading approach for managing data mining, predictive analytic and data science projects. CRISP-DM is effective but many analytic projects neglect key elements of the approach.**90 Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning (updated)**- Jan 17, 2017.

Stay up-to-date in the data science with active blogs. This is a list of 90 recently active blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.**3 ways to learn Data Science at Statistics.com**- Dec 21, 2016.

Get the personal touch you need to deepen your learning with Statistics.com classes that are small, rich and engaging with readings, videos, quizzes, homework, and practical projects, taught online by leading instructors.**IRIS Advanced Engineering: TecnioSpring Data Mining Fellowship**- Dec 21, 2016.

Experienced researcher to carry out different data mining projects with emphasis on industrial applications. This is a 24-month fellowship targeted at persons with a Ph.D. or similar research experience.**KDnuggets™ News 16:n41, Nov 16: Top 10 Amazon Books in Data Mining; Intuitive Explanation of Convolutional Neural Nets**- Nov 16, 2016.

Also An Intuitive Explanation of Convolutional Neural Networks; Data Scientists vs Data Analysts - Part 1; How to Rank 10% in Your First Kaggle Competition.**Top 10 Amazon Books in Data Mining, 2016 Edition**- Nov 11, 2016.

Given the ongoing explosion in interest for all things Data Mining, Data Science, Analytics, Big Data, etc., we have updated our Amazon top books lists from last year. Here are the 10 most popular titles in the Data Mining category.**Agilience Top Data Mining, Data Science Authorities**- Nov 4, 2016.

Agilience developed a new way to find authorities in social media across many fields of interest. We review the top authorities in Data Mining and Data science, which include KDnuggets, Kirk. D. Borne, Kaggle, Vincent Granville, and more.**Ready to take on 2017’s data mining challenges?**- Nov 3, 2016.

With Stanford Graduate Certificates in Data Mining, learn about the applications of mining data within large sets of complex data and how to leverage them into tactical information for your company.**Novel Tensor Mining Tool to Enable Automated Modeling**- Oct 13, 2016.

A tensor - a multidimensional matrix - is ideal for modeling multiaspect data, such as social interactions, which can be characterized by the means of communication, who is interacting, and the time and location of the interaction, for example.**Umea University: Postdoctoral researcher position on Data Mining/Data Federation**- Sep 30, 2016.

Join our efforts to build up Registry Data Federation and Analysis Research Infrastructure. Develop data analysis methods with focus of data federation and privacy preservation.**Data Science Basics: Data Mining vs. Statistics**- Sep 28, 2016.

As a beginner I was confused at the relationship between data mining and statistics. This is my attempt to help straighten out this connection for others who may now be in my old shoes.**Data Science of Reviews: ReviewMeta tool Automatically Detects Unnatural Reviews on Amazon**- Aug 23, 2016.

ReviewMeta is a tool that analyzes millions of reviews and helps customers decide which ones to trust. As the dataset grows, so do the insights on unbiased reviews.**Short course: Statistical Learning and Data Mining IV, Washington, DC, Oct 19-20**- Aug 8, 2016.

This new two-day course gives a detailed and modern overview of statistical models used by data scientists for prediction and inference, including sparse models and deep learning.**KDnuggets™ News 16:n24, Jul 6: Text Mining 101; Softmax and Logistic Regression; Data Mining History: Support Vector Machines**- Jul 6, 2016.

What is Softmax Regression and How is it Related to Logistic Regression; Text Mining 101: Topic Modeling; Data Mining History: The Invention of Support Vector Machines; Mining Twitter Data with Python Part 5: Data Visualisation Basics**History of Data Mining**- Jun 22, 2016.

Data mining is a subfield of computer science which blends many techniques from statistics, data science, database theory and machine learning. Here are the major milestones and “firsts” in the history of data mining plus how it’s evolved and blended with data science and big data.**5 Ways in Which Big Data Can Help Leverage Customer Data**- May 25, 2016.

Every business enterprise realizes the importance of big data but rarely puts the customer data that they possess to good use. Here are few ways enterprises can leverage customer data.**Best Data Science, Machine Learning Blogs from Companies and Startups**- Apr 21, 2016.

A collection of company data science blogs to follow and read. Top blogs have links to, and excerpts from, recent quality posts of particular interest.**SUNY Buffalo: Postdoctoral Associate in Data Mining and Bioinformatics**- Apr 17, 2016.

Developing machine learning and mathematics methodologies to address the computational challenges of analyzing massive genomic data for various biomedical applications.**The Data Science Puzzle, Explained**- Mar 10, 2016.

The puzzle of data science is examined through the relationship between several key concepts in the data science realm. As we will see, far from being concrete concepts etched in stone, divergent opinions are inevitable; this is but another opinion to consider.**scikit-feature: Open-Source Feature Selection Repository in Python**- Mar 3, 2016.

scikit-feature is an open-source feature selection repository in python, with around 40 popular algorithms in feature selection research. It is developed by Data Mining and Machine Learning Lab at Arizona State University.**Umea University: PhD and Postdoctoral positions, Federated Database System/Data Mining**- Feb 9, 2016.

Join our efforts to academic federated database construction and cross-database analysis for research purposes of data from distributed databases. Develop data analysis methods with focus of data integration and privacy preservation.**Webinar: Data Mining: Failure to Launch [Feb 9]**- Jan 26, 2016.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Feb 9.**Webinar: Data Mining: Failure to Launch [Jan 14]**- Dec 15, 2015.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Jan 14.**Top New Features in Orange 3 Data Mining Platform**- Dec 10, 2015.

The main technical advantage of Orange 3 is its integration with NumPy and SciPy libraries. Other improvements include reading online data, working through queries for SQL and pre-processing.**Roche (Basel): Postdoctoral Fellow, Biomedical Text and Data Mining**- Dec 2, 2015.

You will receive scientific mentoring from both Roche and its academic partners, and gain valuable research experience from both academic and industrial perspectives.**University of Tartu, Estonia: Associate Professor of Data Mining**- Nov 13, 2015.

We are looking for candidates with a solid research track record in the fields of data mining and/or machine learning including publications in top venues, and a record of excellence in teaching and student supervision. Apply by Dec 2.**Webinar: Data Mining: Failure to Launch [Nov 10]**- Oct 27, 2015.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Nov 10.**Amazon Top 20 Books in Data Mining**- Oct 27, 2015.

These are the most popular data mining books on Amazon. As you look to increase your knowledge, is there something listed here that is missing from your collection?**DistrictDataLabs Courses on Data Mining, Machine Learning, R, NLP, Social Media, and more**- Oct 17, 2015.

District Data Labs upcoming workshops and courses include Data Mining & Machine Learning with R, Building a Django Data Product, Analyzing Social Media Data with R, and Natural Language Processing with R.**Webinar: Data Mining: Failure to Launch [Sep 23]**- Sep 15, 2015.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Sep 23.**Most popular “Statistical Analysis and Data Mining” Papers**- Sep 9, 2015.

Most popular recent papers from “Statistical Analysis and Data Mining” journal cover They outlier detection, clustering, large-scale analytics, link prediction, mining sequential patterns, and more. They will be free to read for a limited time.**60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more**- Sep 4, 2015.

Here is a great collection of eBooks written on the topics of Data Science, Business Analytics, Data Mining, Big Data, Machine Learning, Algorithms, Data Science Tools, and Programming Languages for Data Science.**RightRelevance helps find key topics, top influencers in Big Data, Data Science, and Beyond**- Aug 11, 2015.

RightRelevance leverages the social web to find key topics and top influencers in many areas, from Big Data to emergency medicine. We use it to identify top influencers in Big Data, Data Science, and Data Mining.**Webinar: Data Mining: Failure to Launch**- Aug 3, 2015.

[Aug 18]

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Aug 18.**New Standard Methodology for Analytical Models**- Aug 3, 2015.

Traditional methods for the analytical modelling like CRISP-DM have several shortcomings. Here we describe these friction points in CRISP-DM and introduce a new approach of Standard Methodology for Analytics Models which overcomes them.**KDnuggets™ News 15:n24, Jul 29: Big Data to Big Profits; Mining Massive Datasets; Data for Humanity**- Jul 29, 2015.

From Big Data to Big Profits: A Lesson from Google's Nest; Coursera/Stanford "Mining Massive Datasets", free online course; Data for Humanity: A Request for Support; To Code or Not to Code with KNIME.**IEEE ICDM 2015 Call For Research and Service Award Nominations**- Jul 17, 2015.

The IEEE ICDM awards recognize influential research contributions to the field of data mining, and major service contributions that have promoted data mining as a field and ICDM as the world premier research conference. Nominations due Aug 15.**Nine Laws of Data Mining, part 2**- Jun 30, 2015.

The second group data mining laws includes: There are always patterns, Data mining amplifies perception in the business domain, Prediction increases information locally by generalisation, Value law, Law of Change. Tom Khabaza explains.**Nine Laws of Data Mining, part 1**- Jun 29, 2015.

Tom Khabaza, one of the authors of the Clementine data mining workbench and of CRISP-DM methodology for data mining process, proposes and explains 9 laws of data mining.**Webinar: Data Mining: Failure to Launch**- Jun 25, 2015.

[July 9]

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is July 9.**Survey: Top Management Support and Data Mining Success**- Jun 21, 2015.

Participate in a research project that investigates if top management support is a contributing factor in making data mining projects successful. Short survey takes 5-10 minutes and results will be published on KDnuggets.**Data Mining and Predictive Analytics Glossary**- Jun 3, 2015.

Here, we have collected definitions of common terminologies used in data science and big data.**Top 10 Data Mining Algorithms, Explained**- May 21, 2015.

Top 10 data mining algorithms, selected by top researchers, are explained here, including what do they do, the intuition behind the algorithm, available implementations of the algorithms, why use them, and interesting applications.**Most Viewed Data Mining Videos on YouTube**- May 18, 2015.

The top Data Mining YouTube videos by those like Google and Revolution Analytics covers topics ranging from statistics in data mining to using R for data mining to data mining in sports.**Last chance – Participate in the Rexer Analytics 2015 Data Miner Survey – before it closes May 30**- May 13, 2015.

Data Analysts, Predictive Modelers, Data Scientists, Data Miners, and all other types of analytic professionals, students, and academics - please participate in the Rexer Analytics 2015 Data Miner Survey before it closes May 30.**Webinar: Data Mining: Failure to Launch**- Apr 27, 2015.

[May 5]

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is May 5.**Data Mining: New Comprehensive Textbook by Charu Aggarwal**- Apr 23, 2015.

This comprehensive data mining textbook explores the different aspects of data mining, from basics to advanced, and their applications, and may be used for both introductory and advanced data mining courses.**Chapter Download from “Data Mining Techniques” (3rd edition)**- Apr 2, 2015.

Download this chapter from "Data Mining Techniques" (3rd Edition), by Gordon Linoff and Michael Berry, and learn how to create derived variables, which allow the statistical modeling process to incorporate human insights.**Top KDnuggets tweets, Mar 23-25: 24 free resources on Data Mining, Data Science; More Training Data or More Complex Models?**- Mar 26, 2015.

24 free resources and online books on #DataMining, #DataScience, #MachineLearning; New R Online Tool for Seasonal Adjustment of time series; Key #DataScience question: More Training Data or More Complex Models?; Twitter #DataMining finds origins of ISIS support.**More Free Data Mining, Data Science Books and Resources**- Mar 25, 2015.

More free resources and online books by leading authors about data mining, data science, machine learning, predictive analytics and statistics.**PACE Data Mining Bootcamps, San Diego, April**- Mar 17, 2015.

Every class is taught by SDSC experienced data scientists, delivering practical, hands-on training in an intimate classroom setting limited to 25 participants. Early bird till Mar 31.**Upcoming Webcasts on Analytics, Big Data, Data Science – Mar 17 and beyond**- Mar 16, 2015.

Predictive Analytics - Rethinking Big Data, Addressing the Challenges of Data Variety, Semantic Publishing for News & Media, Data Mining: Failure to Launch.**IEEE ICDM 2015 Call for Papers, Workshops, Contest proposals, demos, and tutorials**- Mar 16, 2015.

ICDM '15: The 15th IEEE International Conference on Data Mining, a leading research conference in the field, calls for workshop proposals, contest proposals, papers, demo proposals, and tutorial proposals. Conference dates: Nov 14-17, Atlantic City, NJ, USA.**KDD-2017, top conference on Data Mining, Data Science Research coming to Halifax, Canada**- Mar 10, 2015.

The 2017 edition of KDD, the leading conference on Knowledge Discovery, Data Mining, and Data Science Research will be held in Halifax, Nova Scotia, Canada.**Webinar: Data Mining: Failure to Launch [Mar 11]**- Mar 9, 2015.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Mar 11.**Chapter Download from “Data Mining Techniques”**- Mar 9, 2015.

Download this chapter from "Data Mining Techniques" (3rd Edition), by Gordon Linoff and Michael Berry, and learn how to create derived variables, which allow the statistical modeling process to incorporate human insights.**IEEE ICDM 2015 Call for Data Mining Contest/Competition Proposals, due Mar 29**- Feb 28, 2015.

We invite proposals for the ICDM 2015 Data Mining Contest, which is an integral part of the IEEE ICDM conference and provides an opportunity for teams of scientists and domain experts to compete in order to develop data mining techniques for real-world applications.**TU/e: Full Professor in Data Mining**- Feb 26, 2015.

You have the opportunity to set up your own research group, complementary to 2 existing groups - one focusing on business process management and process mining, and another focusing on web engineering, data mining, and databases.**Active Data Mining, Data Science blogs**- Feb 16, 2015.

Here are 85 or so active (recently updated) data mining, data science, and machine learning blogs.**Info Kit: Statistics, Predictive Modeling, Data Mining with JMP**- Feb 10, 2015.

Find out how to challenge assumptions, spot patterns and reveal potential solutions to problems that otherwise would not be visible. Register for this complimentary info kit.**Stanford Online Courses: Use data to solve biological, medical problems**- Feb 10, 2015.

Stay at the cutting-edge and take courses online from Stanford that will teach you techniques used in new applications in biomedicine. Enrollment for spring open till Mar 20.**Webinar: Data Mining: Failure to Launch [Feb 10]**- Feb 3, 2015.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Feb 10.**PACE Data Mining Boot Camps, San Diego, Feb 10-11**- Jan 10, 2015.

San Diego Supercomputing Center PACE (Predictive Analytics Center of Excellence) excels at delivering practical, hands-on training in a small classroom setting. Attend next data mining boot camp is Feb 10-11.**Differential Privacy: How to make Privacy and Data Mining Compatible**- Jan 9, 2015.

Can privacy coexist with machine learning and data mining? Differential privacy allows the learning of general characteristics of populations while guaranteeing the privacy of individual records.**Webinar: Data Mining: Failure to Launch [Jan 15]**- Jan 5, 2015.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Jan 15.**BIME Business Intelligence Predictions for 2015**- Dec 26, 2014.

Business intelligence in 2015 will see greater social media involvement, data mining applications, health data analysis, data-driven drones, and BI in the cloud.**Data Mining (and Statistical Analysis) is LinkedIn Hottest Skill in 2014**- Dec 18, 2014.

Data Mining was LinkedIn Hottest Skill in 2014, moving up from number 5 in 2013. Top locations for "data mining" skill were US, India, Australia, and Canada, while top companies were IBM, Microsoft, Google, and Accenture.**Where Analytics, Data Mining, Data Science is applied**- Dec 9, 2014.

CRM/Consumer analytics, Banking, and Health care are the most popular industries, but also joined by new sectors including Oil / Gas / Energy, Automotive, and HR/workforce analytics.**Webinar: Data Mining: Failure to Launch [Dec 17]**- Dec 9, 2014.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Dec 17.**Webinar: Data Mining: Failure to Launch [Dec 17]**- Nov 24, 2014.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Dec 17.**EURECOM: Faculty Position in Data Mining and Machine Learning**- Nov 20, 2014.

EURECOM, graduate school and a research center in communication systems, seeks qualified applicants interested in Big Data and Cloud computing for a tenured assistant professor position.**Companion Website for “Data Mining and Analysis: Fundamental Concepts and Algorithms”**- Nov 19, 2014.

Supplementary materials for the textbook Data Mining and Analysis: Fundamental Concepts and Algorithms are now available online and include figures, slides, datasets, videos, and more. Download them today.**CRISP-DM, still the top methodology for analytics, data mining, or data science projects**- Oct 28, 2014.

CRISP-DM remains the most popular methodology for analytics, data mining, and data science projects, with 43% share in latest KDnuggets Poll, but a replacement for unmaintained CRISP-DM is long overdue.**Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 28 and beyond**- Oct 27, 2014.

DM Radio: Predictive Tools Are Pervasive - with Gregory Piatetsky (KDnuggets), Predixion, others; Deep Learning + Apache Spark; Data Mining - Failure to Launch; Demystify your data flows, Data hiding, and more.**Book: Data Mining for Managers**- Oct 14, 2014.

This book by a leading data mining consultant is meant for both practitioners and end users of data mining solutions, and it focuses more on the data and less on the math.**SPOTLIGHT: Can Data Science Save Humanity from Mosquitoes and other Deadly Insects? #2**- Oct 9, 2014.

KDnuggets launches Spotlight initiative to bring attention to academic research. The journey begins with Prof. Eamonn Keogh, UCR and his talented student, Yanping Chen, who are applying data mining to save us all from insect-vectored diseases.**SPOTLIGHT: Can Data Science Save Humanity from Mosquitoes and other Deadly Insects?**- Oct 8, 2014.

KDnuggets launches Spotlight initiative to bring attention to academic research. The journey begins with Prof. Eamonn Keogh and his student, Yanping Chen, who are applying data mining to save us all from insect-vectored diseases.**Webinar: Data Mining: Failure to Launch [Oct 16]**- Oct 7, 2014.

Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Oct 16.**Predictive Analytics Using Oracle Data Miner**- Sep 24, 2014.

Learn about basic data mining concepts and how to apply data mining techniques to your data using Oracle SQL and Data Miner tools in this new book.**PACE Data Mining Boot Camps, Oct 15-16, San Diego**- Sep 23, 2014.

The PACE Boot Camps provide conceptual and hands-on training for the critical predictive data analytics techniques that help discover actionable patterns in Big Data. Reg by Oct 10 for a discount.**Upcoming Webcasts on Analytics, Big Data, Data Science – Sep 22 and beyond**- Sep 22, 2014.

Future of Hadoop Analytics, What Works: Open Source Analytics Software, Data Mining: Failure To Launch, Evolution of Classification, Not all Graph Databases are created equal, Best Practices for Applying Advanced Analytics in Hadoop, and more.**Customer Analytics Summit 2014 Chicago: Day 2 Highlights**- Sep 12, 2014.

Highlights from the presentations by Big Data & Analytics experts from Microsoft, Sears Holdings and Obama for America on day 2 of Customer Analytics Summit 2014.**Hiring Data Scientists: What to look for?**- Sep 9, 2014.

Know key characteristics of what makes up a good data scientist based upon the three authors’ consulting and research experience, having collaborated with many companies world-wide on the topics of big data and analytics.**Most Viewed Data Mining Talks at Videolectures**- Sep 9, 2014.

Watch the top 25 most viewed popular data mining lectures on VideoLectures.NET to learn about topics ranging general big-data tutorials to monetizing data mining startups.**Sep 2014 – Mar 2015 Meetings in Analytics, Big Data, Data Mining, and Data Science**- Sep 3, 2014.

Coming soon: PAW Gov, ECML/PKDD, BayesiaLab UC, Big Data Innovation Summit, PAW Boston, PAW Healthcare, RecSys, Strata + Hadoop NYC, Analytics 2014, BigData TechCon, Data Analytics Week, Text Analytics Summit West,and many more.**Webcast – Analytically Speaking Featuring Michael J. A. Berry and Gordon S. Linoff**- Sep 2, 2014.

Berry and Linoff talk about the current data mining landscape, including new methods, new types of data and the importance of using the right analysis for your problem.**KDD-2014 – The Biggest, Best, and Booming Data Science Meeting**- Aug 28, 2014.

KDD-2014 was the largest (with over 2300 people) and the best Data Science meeting, highlighting the huge progress of Data Science made with Big Data, and its even more amazing potential.**DataReview interview with me on KDnuggets, Data Mining, and Data Science**- Aug 20, 2014.

I have recently given an interview to DataReview, an Ukrainian site, where we talked about KDnuggets origins, history of Data Mining, interesting problems I worked on, and typical problems faced by young data scientists.**KDnuggets 14:n22, 4 main analytics languages; Top research leaders in Data Mining; Pedro Domingos**- Aug 20, 2014.

KDnuggets Analytics, Big Data, Data mining, and Data Science stories, including Features, News, Opinions, Interviews, Webcasts, Courses, Meetings, Jobs, Publications, and Top Tweets.**Upcoming Webcasts on Analytics, Big Data, Data Science – Aug 19 and beyond**- Aug 18, 2014.

Data Mining: Failure To Launch, Smart Metering, Hadoop, Data Science at the Command Line, Personalized Healthcare, Modern Regression Analysis Techniques, and more.**Four main languages for Analytics, Data Mining, Data Science**- Aug 18, 2014.

New KDnuggets Poll shows the growing dominance of four main languages for Analytics, Data Mining, and Data Science: R, SAS, Python, and SQL - used by 91% of data scientists - and decline in popularity of other languages, except for Julia and Scala.**Top KDnuggets tweets, Aug 15-17: Top Research Leaders in Data Mining; Hbase; Job Interview**- Aug 18, 2014.

The top 5 Questions a Data Scientist should ask during a job interview; Top Research Leaders in Data Mining, Data Science, and KDD; Least popular jobs for big data practitioners; Graduate Programs in #BigData Analytics and Data Science.**Top Research Leaders in Data Mining, Data Science, and KDD**- Aug 16, 2014.

We identify the top researchers in Data Mining, Data Science, and KDD. Jiawei Han, Philip Yu, and Christos Faloutsos remain the leaders, but they are joined by many fast rising young researchers - the leaders of tomorrow.**Statistical Learning and Data Mining III, Boston, Oct 27-28**- Aug 14, 2014.

Taught by top Stanford professors and leading statisticians Trevor Hastie and Robert Tibshirani, this course presents 10 hot ideas for learning from data, and gives a detailed overview of statistical models for data mining, inference and prediction.**New Poll: What languages you used for analytics / data mining / data science work in 2014?**- Aug 6, 2014.

New KDnuggets Poll is asking: What languages you used for analytics / data mining / data science work in 2014? Please vote.**Upcoming Webcasts on Analytics, Big Data, Data Science – Aug 5 and beyond**- Aug 4, 2014.

Hadoop and Relational DB, Seductiveness of Big Data, SAS to R, Data Mining: Failure To Launch, Personalized Healthcare, Data Science at the Command Line, and more.**Top KDnuggets tweets, Jul 30-31**- Aug 1, 2014.

What are the differences between Data Science, Data Mining, Machine Learning, etc; Where do the most romantic US singles live?; 7 signs you're too smart for the job? Not a #BigData problem; Guidelines for statistical education.