A recent post has generated an intense discussion about finding "unicorn" data scientists with a combination of all the needed skills, or whether that skillset is best filled by a team. Here are the highlights, including a proposal how to train well-rounded data scientists.
Data Mining Applications with R; "Data Scientist" catches up with "Statistician", surpasses "Data Miner"; What is Wrong with the Definition of Data Science;
Most popular datasets on Reddit include NFL Game Metadata, Reddit top 2.5 Million posts, Zillow housing prices, and, of course, a database of cat pictures.
KU Leuven has a postdoc fellowship: Knowledge Acquisition for Automated Natural Language Understanding position, and PhD position: Intelligent Aids for Multilingual Information Processing.
Data science is permeating every facet of our daily lives - from our culture to our classrooms. Look for data science to make an even greater impact in 2014.
The emergence of Apache Spark is a key development for Big Analytics; 5 Free Excel add-Ins to help Marketers analyze #BigData; Key Skills of Top @kaggle Competitors: R (90%), Random Forests (60%); Netflix open sources Suro: data traffic "cop" which directs #BigData to destination
Key themes were: Customer Obsessed Marketer, Segment of One, SoLoMo (Social, Local and Mobile), and Big Data - actionable insights and decision making.
New bold predictions include: More Hadoop projects will fail than succeed, The need for automated tools will become critical, and #BigData will fly to the cloud.
New book: Data Mining Applications with R; Data Scientist catches up with Statistician; What is Wrong with the Definition of Data Science; Making sense of #BigData : mining Twitter names
A veteran statistician argues that 3 different areas usually included in "Data Science" require dramatically different, skills, education, and training with very little overlap.
Data Mining Book Review: "Visualize This" from @flowingdata; Top NYU Professor Vasant Dhar on Data Science and Prediction - what do they mean; Analysis reveals #MOOC problems: student participation drops dramatically.
Covers 15 real-world applications on data mining with R, including R code and data, covering business background and problems, data extraction and exploration, data preprocessing, modeling, model evaluation, findings and model deployment.
The rapidly rising term "Data Scientist" caught up with "Statistician" and surpassed "Data Miner" on Google Trends. However, Statistics remains a lot more popular than "Data Science", which begs the question: What do Data Scientists do? Clearly, it is not Data Science.
DMCS (Data Mining Case Studies) 2013 Practice Prize was awarded at ICDM 2013 conference for a work on a novel and successful credit card fraud detection system, implemented in a Turkish bank. The Prize was partially sponsored by KDnuggets.
Poll Results: R has a big lead, but Python is gaining; Top 2013 LinkedIn Groups for Analytics, Big Data; Predictive Analytics in 2014: Monetizing, Not Managing Big Data
What does "Data Science" and #BigData mean? Is there something unique about it? What skills do "data scientists" need to be productive in a world deluged by data? What are the implications for scientific inquiry?
Analytically sophisticated businesses combine predictive analytics and decision models with optimization to solve complex problems and achieve good results. Top FICO expert explains.
Help with the real-time prototyping of The Tower Project, which monitors and aims to predict natural and man-made disasters by looking at data such as volume of calls and SMS.
Partner with business teams to understand objectives and scope analytical projects that deliver insights and results; work in a cross-functional manner with other consultants, analysts, statisticians, data engineers, and external vendors to deliver insights and solutions.
Poll Results: R has a big lead, but Python is gaining; Who are Data Scientists and why they are or are not unicorns; 2014 Predictions: Machine-generated data will grow; #BigData + Big Pharma = Big Privacy Catastrophe
SEARCH is a statistical technique for understanding complex interactions among explanatory variables in describing a wide variety of phenomena. Awards for US grad students/postdocs trying to understand complex interactions in large databases.
Be instrumental in defining, driving and extending the vision for WhitePages data and help identify new ways to improve the value of our data by through freshness, accuracy, breadth, and depth.
Poll results show that R has a big lead, but Python is gaining among data scientists; We re-analyze top LinkedIn Groups for Analytics, Big Data and Data Science; Top 2013 Stoeries on KDnuggets and more.
More people than ever are interested in how big data and analytics can give them an edge. Watch the panelists, Gregory Piatetsky-Shapiro, Editor of KDNuggets, and Michael Karasick, VP of research in IBM acclaimed Almaden Research as they delve into these topics and give us a look at what they think will be the hottest topics and developments of 2014.
Guest blog of SkyTree CEO Martin Hack looks at 2 Key Trends in Predictive Analytics in 2014: high performance machine learning will penetrate the mainstream, and privacy issues associated with Big Data will be debated by business owners and consumers alike.
Help improve the achievement of students nationwide by supporting our K-12 assessment and professional development programs, by defining and implementing the statistical analysis processes.
Predictive analytics professionals will not want to miss the PAW keynote speakers. Register by Jan 24 with Early Bird Pricing and get the best deal on analytics networking.
A billion rows per second in Python; #BigData Dashboard Dizziness - what you get after careful consideration of 437 charts; Import.io turns any website into a database; 2014 Predictions: Machine-generated data
Extract insights from complex media usage data sets for product development, identify strategic opportunities, and become the expert for digital metrics - dream job for a public radio lover.
The course features video lectures by Professor Ian H. Witten, with English & Chinese subtitles, open-source Weka data mining platform. What were the most interesting lectures?
Help build the most exciting startup in Europe! DueDil answers the needs of the largest and fastest growing user base of B2B decision makers in the UK and is becoming the data backbone of business.
Highlights of the IEEE ICDM 2013 Conference on Data Mining: Good organization in icy conditions, How to do clustering in high dimensions, Discovering unexpected sequential patterns, and perspectives on #BigData.
Focus on teaching (mainly undergraduate, some MBA and certificate programs), provide tudents with a strong foundation in marketing concepts and introduce them to cutting edge marketing tools.
Salary of Analytics/Data Science professionals; Top Languages for analytics, data mining, data science; 7 Steps for Learning Data Mining and Data Science; Book: Twitter Data Analytics - free download
Seeking methodology for quantifying the value of different types of business data in order to inform large scale investment decisions concerning improving data infrastructure, supply chain and management.
Facebook hires Deep Learning expert Yann LeCun to head its new AI lab; New Data Mining and Machine Learning books from CRC Press - Save 25%; Import.io turns any website into a database; 2014 World Cup Group Stage, per ESPN: Brazil, Argentina, Germany, France advance
Novel and interesting use cases of Oracle Big Data, Exadata, Advanced Analytics/Data Mining, Endeca; opportunities to get hands-on experience; great customer case studies and more.
New Book: A Programmer Guide to Data Mining - Free Download; 3 Stages of Big Data; New Poll: Did you switch between R, Python, or other Data Science Languages? Top LinkedIn Groups for Analytics, Big Data
Develop and investigate hypotheses, structure experiments and build mathematical models to identify game optimization points that will encourage users to play our games more.
Written by leaders in the data mining community, this new book provides an in-depth introduction to the application of data mining and business analytics techniques and tools in scientific research, medicine, industry, commerce, and diverse other sectors.
Save 25% on new books Data Mining and Machine Learning books, including Multilinear Subspace Learning, Bayesian Programming, Computational Business Analytics, and Multi-Label Dimensionality Reduction.
More fuel thrown into Data Science Wars: Python vs. R; Data Science Toolbox virtual environments for command-line data science; T-index is like academic H-index; Movie Analytics in India: Dhoom 3 to Don 3
We revisit our analysis of top 30 LinkedIn groups for Analytics, Big Data, Data Mining, and Data Science and identify the largest, fastest growing, and most active groups. In 2013 the growth rate of top groups more than doubled, and growth rate correlated with the activity level.
Data Science Toolbox: a new virtual environment for command-line data science - how it compares with similar environments: Mining the Social Web, Data Science Toolkit, and Data Science Box.
The LIONbook on machine learning and optimization, written by co-founders of LionSolver software, is provided free for personal and non-profit usage. Chapter 17 looks at Semi-supervised learning.
The LIONbook on machine learning and optimization, written by co-founders of LionSolver software, is provided free for personal and non-profit usage. Chapter 16 looks at Visualizing graphs and networks by nonlinear maps.
Predictive Analytics and Game theory can help answer questions like Can Dhoom 3 or Don 3 be as successful as Mother India, or which actor should have the main role for movie to be successful.
Discovering innovative approaches to leveraging advanced statistical and econometric modeling techniques to perform marketing mix modeling research on multiple massive datasets.
Research the next generation digital marketing applications and products using large-scale machine learning, statistical-relational modeling, location prediction and social networks analysis.
Highlights include Focus on CRM, Big Data perhaps not so big, The Ascendance of R, Challenges in the use of analytics, High Job Satisfaction, and a ranking of analytics software by several measures, including Ease-of-use and cost.
European Travel Patterns; Cloudera resources for Data Science beginners; New Book: A Programmer Guide to Data Mining - free download; 3 stages of Big Data to help clarify the confusion
Work with product, business, community and development teams to define, analyze and refine KPIs for overall product and new features. Drive the creation of a robust analytics tech stack to log and analyze all product data.
New Poll: Did you switch between R and Python; 3 Stages of Big Data; Why statistical community is disconnected from Big Data and how to fix it; Why RapidMiner? By Usama Fayyad; and more analytics/data mining news
This book provides an in-depth introduction to the application of data mining and analytics techniques in science, medicine, industry, commerce, and other sectors.
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 18.
The MS in Predictive Analytics at DePaul University addresses the growing demand for data scientists with 4 timely and in-demand concentrations: Marketing, Computational Methods, Hospitality, and Health-Care Analytics.
From power tools to automobiles, health monitoring machines to wind turbines, our Big Data group is focused on using expertise in data mining and machine learning to improve lives through our products.
New book "A Programmer Guide to Data Mining" - a guide to practical data mining, collective intelligence, and building recommendation systems by Ron Zacharski. Free download of all chapters.
Predictive analytics professionals will be beating down the doors of this international conference to hear from PAW keynote speakers. Dont miss your chance to save on PAW registration - register by Jan 24 with Early Bird Pricing.
The goal of this challenge is to encourage innovative visualizations of web data, especially interdisciplinary approaches. Use any of 4 huge datasets: web traffic, Twitter data, social bookmarking, or academic co-authorship.
A public list of R #rstats freelancers - great resource; Top 10 Big Ideas in Harvard Statistics Class; 3 stages of Big Data to help clarify the confusion; Trifacta, maker of #BigData platform for machine-learning powered data visualization
New KDnuggets Poll focuses on on the controversy around whether Python displaces R as language for Data Science, or whether R remains the dominant language. Please vote if you switched between R, Python, or other data analysis language in 2013.
The confusion around Big Data is partly the result of different aspects of Big Data which have very different meaning and produce very different results. We propose a 3 stage classification.
Harvard CS109 Data Science Course, Resources Free and Online; Open Source Data Science Masters Curriculum; Gates Foundation Grants: Big Data for Social Good; Statistical Community and Big Data disconnect
The Big Ideas in Statistics include: Conditioning (the soul of statistics), Random variables and random vectors, Stories, Symmetry, Linearity of expectation, LOTUS, Variance, covariance, and correlation.
Candidates should have a Ph.D. in Information Systems, Informatics, Information Science, Computer Science, Management Science or a related field and exhibit exceptional research and teaching promise.
R is great for stats on one file, but for more complex data analysis use Python; How Facebook own Edgerank algorithm is killing it; Gates Foundation awards grants for using Big Data for Social Good; Preview of book Data Mining Applications with R
Highlights from a vigorous discussion on Statistical community and Big Data, including: Are data scientists reinventing statistics? Did statisticians miss the boat in 1990s? Is more data always better? Statistics 2.0?
Bruce Ratner examines how to combine skills acquired by experience (art) and a technique that reflects a precise application of fact or principle (science).
With the current release of RapidMiner v6, and the introduction of application wizards to help business analysts instantly work with their data, RapidMiner will continue to be the platform of choice for anyone analyzing Big Data.
The November 2013 acquisitions, startups, and company activity in Analytics, Big Data, Data Mining, and Data Science: KPMG $100M fund, Jut, Alpine Data, RapidMiner, BIME Analytics
Google "Deep Learning" is outsmarting its human employees; Udacity Creates Online Degree Program For Data Science; JSON and #BigData will Shape the Internet of Things: RESTful APIs a key component; The Case Against #BigData In Sports
This certificate program brings together the computational, analytical and communication skills necessary to discover and implement data-supported solutions to business questions. Classes run Feb 13-May 22.
The Eric & Wendy Schmidt Data Science for Social Good 2014 Summer Fellowship at the University of Chicago is looking for students, mentors, and project partners - apply by Feb 1.
RedButtonSolver shows how to get insight from your data without a PhD in Statistics, by following 3 simple steps and giving you answers, including great visualizations, to 5 key business questions.
Working on high impact, real world problems using huge (and somewhat messy) data sets, including billions of transactions, to unlock valuable insights and power new products for the New York Times.
The 2013 Yahoo! Fellow Kalev Leetaru talks about Big Data, Global Diplomacy and Digital Heartbeat and application of Big Data to understanding international relationships.
Harvard CS109 Data Science Course, Resources Free and Online; Cartoon: Thanksgiving, Big Data, and Turkey Data Science; Yahoo SAMOA, Open Source Platform for Mining Big Data Streams
Open Source Data Science MS Curriculum; 5 ways to handle #BigData in R; Yahoo SAMOA, Open Source Platform Mining Big Data Streams; 3 Levels of Data: fits in Excel; fits in RAM; a world of pain
CIO Review special report on 20 Most Promising Data Analytics Companies, which cover Big Data, real-time insights, enterprise analytics, employee analytics, health care, and even neuroscience based data analytics.
A good collection of open source resources for Data Science Masters Curriculum, covering Math, Algorithms, Databases, Data Mining, Machine Learning, Natural Language Processing, Data Analysis and Visualization, and Python.
Harvard Data Science Course, free resources online; Field Guide to Data Science - free download; WDC Huge Web Graph; Cartoon: Thanksgiving, Big Data and Turkey Data Science
Nov
Unicorn Data Scientists vs Data Science Teams - Dec 30, 2013.A recent post has generated an intense discussion about finding "unicorn" data scientists with a combination of all the needed skills, or whether that skillset is best filled by a team. Here are the highlights, including a proposal how to train well-rounded data scientists.
