Data Natives 2015: A Conference for the Data-Driven Generation, Berlin, Nov 19-20
Data Natives celebrates three areas of technology that are driving innovation and the next wave of billion dollar startups. Join industry leaders from Big Data, IoT and FinTech.
on Oct 30, 2015 in Berlin, Fintech, Germany, IoT, Kirk D. Borne
How Big Data is used in Recommendation Systems to change our lives
A Recommendation systems have impacted or even redefined our lives in many ways. It works in well-defined, logical phases which are data collection, ratings, and filtering.
on Oct 30, 2015 in Amazon, Big Data, Kaushik Pal, Recommendations, Recommender Systems
October Academic Positions in Analytics, Data Mining, Data Science, Machine Learning
Academic and research positions at PNNL, U. of Arizona, UCSC, Eastern Michigan University, Florida Institute of Technology, USF CA, UIC, and U. of Iowa.
on Oct 30, 2015 in PNNL, U. of Arizona, UCSC, UIC, University of Iowa, University of San Francisco
Integrating Python and R, Part 2: Executing R from Python and Vice Versa
The second in a series of blog posts that: outline the basic strategy for integrating Python and R, we will concentrate on how the two scripts can be linked together by getting R to call Python and vice versa.
on Oct 30, 2015 in Python, Python vs R, R
A Neural Network in 11 lines of Python
A bare bones neural network implementation to describe the inner workings of back-propagation.
on Oct 30, 2015 in Backpropagation, IPython, Neural Networks, Prediction, Python
The Human Element of Data Science
About 100 data scientists gathered for the first ever WrangleConf (hosted by Cloudera) to explore the topic of the importance of humans throughout the data science process.
on Oct 29, 2015 in Data Science, Human Intelligence, Mode Analytics
Integrating Python and R into a Data Analysis Pipeline, Part 1
The first in a series of blog posts that: outline the basic strategy for integrating Python and R, run through the different steps involved in this process; and give a real example of how and why you would want to do this.
on Oct 29, 2015 in Data Analysis, Mango Solutions, Python, Python vs R, R
We need a statistically rigorous and scientifically meaningful definition of replication
Replication and confirmation are indispensable concepts that help define scientific facts. It seems that before continuing the debate over replication, we need a statistically meaningful definition of replication.
on Oct 29, 2015 in Replication, Reproducibility, Statistics
Data Science of IoT: Sensor fusion and Kalman filters, Part 1
The Kalman filter has numerous applications, including IoT and Sensor fusion, which helps to determine the State of an IoT based computing system based on sensor input.
on Oct 29, 2015 in FutureText, IoT, Kalman Filters, Sensors
An Inside View of Language Technologies at Google
Learn about language technologies at Google, including projects, technologies, and philosophy, from an interview with a Googler.
on Oct 29, 2015 in Google, NLP, Text Analytics
SAS Adds Certifications for Big Data and Data Science
SAS has been in the business of analytics and data science for long time, this new offering comes at an opportune time as big data technologies are requiring new skills and demand for analytical talent is at an all-time high.
on Oct 28, 2015 in CA, Certification, Data Science, Data Science Certificate, New York City, NY, San Francisco, SAS
Deep Learning Finds What Makes a Good #selfie
Ever wonder how a convolutional neural network would rate your selfies? Well, wonder no more!
on Oct 28, 2015 in Andrej Karpathy, Convolutional Neural Networks, Deep Learning, Matthew Mayo, Selfie
Explaining Analytics to Decision Makers: Insights to Actions
Communicating the value of analytics work requires different tools and skills than building predictive models, but you need to master these tools to have your work implemented.
on Oct 27, 2015 in Analytics, DC, Jeff Zeanah, New York City, NY, SAS, Skills, Washington
Top KDnuggets tweets, Oct 20-26: Why Self-Driving Cars Must Be Able to Kill: an impossible dilemma of algorithmic morality
Why Self-Driving Cars Must Be Able to Kill: an impossible dilemma of algorithmic morality; Cartoon: KDnuggets Addiction; Good overview: #BigData Infrastructure at IFTTT.
on Oct 27, 2015 in Cars, Deep Learning, Fraud Detection, Nobel, Self-Driving Car
Webinar: Data Mining: Failure to Launch [Nov 10]
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.
on Oct 27, 2015 in Data Mining, Failure to Launch, The Modeling Agency, TMA
Amazon Top 20 Books in Data Mining
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?
on Oct 27, 2015 in Amazon, Book, Data Mining
Saint Mary’s Mathematically Rigorous MS in Data Science, Primarily Online
At Saint Mary's you'll develop a strong mathematical base, an enduring skill set in an ever-changing world, that will allow you to take on complex data challenges now and in the future. Apply by Dec 1.
on Oct 27, 2015 in IN, Master of Science, MS in Data Science, Notre Dame, Online Education, Saint Mary's College
Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 27 and beyond
Amazon QuickSight, Textual Healing, What's new in Statistica 13, Real-time Hadoop and IoT, Ad Hoc Visual Discovery, and more.
on Oct 26, 2015 in Amazon QuickSight, Dell, IoT, Ontotext, Realtime Analytics, Statistica, Text Analytics
You’ve Read the Book, Now Listen to the Podcast
Podcasts are a great way to enhance your education without sacrificing precious time. Here are six of the best data-science-oriented podcasts to listen to if you’re a fan of popular data science books.
on Oct 26, 2015 in Book, FiveThirtyEight, Freakonomics, Podcast, SMU
OpenText Data Digest Oct 23: World Statistics Day
This week we look at 3 top entries in the UN competition based around eight Millennium Development Goals to see how well they stack up against the data visualizations you are working on.
on Oct 26, 2015 in Data Visualization, OpenText, Statistics, United Nations
Introducing: Blocks and Fuel – Frameworks for Deep Learning in Python
Blocks and Fuel are machine learning frameworks for Python developed by the Montreal Institute of Learning Algorithms (MILA) at the University of Montreal. Blocks is built upon Theano (also by MILA) and allows for rapid prototyping of neural network models. Fuel serves as a data processing pipeline and data interface for Blocks.
on Oct 26, 2015 in Deep Learning, Jim O' Donoghue, Python, Theano
Random vs Pseudo-random – How to Tell the Difference
Statistical know-how is an integral part of Data Science. Explore randomness vs. pseudo-randomness in this explanatory post with examples.
on Oct 26, 2015 in Correlation, Random
Top stories for Oct 18-24: R vs Python: head to head data analysis; Big Data + Wrong Method = Big Fail
R vs Python: head to head data analysis; The Best Advice From Quora on How to Learn Machine Learning; Big Data + Wrong Method = Big Fail; Infographic - Data Scientist or Business Analyst? Knowing the Difference.
on Oct 25, 2015 in Top stories
Cartoon: KDnuggets Addiction
New Cartoon looks at a serious case of KDnuggets addiction and what can be done about it.
on Oct 24, 2015 in About KDnuggets, Cartoon
New Books on Accelerating Discovery, Event Mining, Networking for Big Data
New books cover important Data Science topics, including Mining Unstructured Information for Hypothesis Generation, Event Mining, and Networking for Big Data. Use GZP42 to save 20%.
on Oct 23, 2015 in Big Data, Book, CRC Press, Event Mining, Network Science, Process Mining, Unstructured data
How to Use Data Visualizations to Win Over Your Audience
Any credible media services require a scientific insights, generated by the support of any case more than cold, hard, unbiased data. In this post, you will learn how to use data visualizations to win over your audience.
on Oct 22, 2015 in Dashboard, Data Visualization, Maptive
Data Science Programming: Python vs R
With every industry generating massive amounts of data – the need to crunch data requires more powerful and sophisticated programming tools like Python and R language.
on Oct 22, 2015 in DeZyre, Python, Python vs R, R
The Data Science Machine, or ‘How To Engineer Feature Engineering’
MIT researchers have developed what they refer to as the Data Science Machine, which combines feature engineering and an end-to-end data science pipeline into a system that beats nearly 70% of humans in competitions. Is this game-changing?
on Oct 22, 2015 in Automated, Data Science, Feature Engineering, Feature Extraction, MIT
Unlock the Power of Spark with IBM Watson and Twitter
Spark is everywhere, including in IBM's cloud infrastructure. Read up on using Spark for Twitter analysis, and how it fits in with Watson and BlueMix.
on Oct 22, 2015 in Apache Spark, IBM, Twitter, Watson
There is a new Statistica in town – Oct 29 Webinar
Dell unveils all the cool, new features in Statistica 13 in Oct 29 webinar - reserve your place.
on Oct 22, 2015 in Dell, Statistica
Spark + SETI: Amping up Spark SQL with Parquets
Spark SQL is a great component for data scientists as it simplifies the querying large distributed datasets. Learn how to integrate it with Parquets, which we have found to significantly improve the performance of sparse-column queries.
on Oct 21, 2015 in Apache Spark, IBM, Parquets, Python, SETI, Spark SQL, SQL
OpenText Data Digest, Oct 16: Millennial Parenting
Time Magazine’s latest cover story on the trends in Millennial parenting is chocked full of data about the way the younger generation—those born after 1985—approaches their childrearing duties. We’re offering some perspective on the issue.
on Oct 21, 2015 in Data Visualization, OpenText
2015 Updated Analytics Compensation and Demographics
Burtch Works Study recently released updated salaries and demographic information on 1,757 Predictive Analytics Professionals (PAPs) across the US which include the work experience, residency, education and etc.
on Oct 21, 2015 in Burtch Works, Data Science, Salary
Top KDnuggets tweets, Oct 13-19: R vs Python: head to head; Machine Learning for Developers tutorial
Machine Learning for Developers - very nice tutorial; R vs #Python: head to head #Data Analytics; Data Science Skills and the Improbable Unicorn Data Scientist; How Tesla AutoPilot learns.
on Oct 20, 2015 in Machine Learning, Pedro Domingos, Python vs R, Scala, Tesla, Tutorials
MetaMind Mastermind Richard Socher: Uncut Interview
In a wide-ranging interview, Richard Socher opens up about MetaMind, deep learning, the nature of corporate research, and the future of machine learning.
on Oct 20, 2015 in Convolutional Neural Networks, Deep Learning, Image Recognition, MetaMind, Recurrent Neural Networks, Richard Socher, Zachary Lipton
RE.WORK Connect: Shaping a Hyper-connected World
RE.WORK Connect Summit (San Francisco, Nov 12-13), is a unique opportunity to meet with business leaders, influential technologists and entrepreneurs leading the IoT revolution. Use KDNUGGETS code for 20% off.
on Oct 20, 2015 in CA, Cars, IoT, RE.WORK, San Francisco, Smart City, Wearables
TMA Predictive Analytics Data Mining Training [San Jose, Dec 7-11]
Successful analytics in the big data era does not start with data and software, but with hands-on, immersive training and goal-driven strategy - get it from The Modeling Agency in San Jose, Dec 3-4 or Orlando in February.
on Oct 20, 2015 in CA, Data Mining Training, San Jose, The Modeling Agency, TMA
New Poll: Should Data Science Include Ethics Training?
New poll is examining the question of Ethics and Data Science. Are Data Scientists more like physicians who take The Hippocratic Oath or more like Mathematicians, who work with numbers? Please vote.
on Oct 20, 2015 in Data Science, Ethics, Poll
Infographic – Data Scientist or Business Analyst? Knowing the Difference is Key
Infographic depicting unique differences between data scientists and business analysts. Find out what type of professional is needed to meet your organization’s needs.
on Oct 20, 2015 in Business Analyst, Data Scientist, Education, Infographic, Jobs
Lavastorm – 5 Tips to Get More From Tableau
Tableau makes it easy for users to see the data, but data preparation for it is hard. This free ebook highlights how to overcome Tableau challenges with data access, data blending, advanced analytics, transparency and reusability.
on Oct 20, 2015 in Data Preparation, Free ebook, Lavastorm, Tableau
Lets talk about Ethics in Analytics / Data Science
Is it time that data scientists go through formal ethics training? The saying “Lies, damned lies, and statistics” suggests that statistics (and Data Science) can be tweaked to prove any point and ethics training will help to improve the integrity and credibility of analytics profession.
on Oct 20, 2015 in Bhasker Gupta, Data Science, Ethics, Statistics
Trick-or-Treat a Data Scientist
How would one infuse Data Science skills in children to optimize candy collection on Halloween? Zeeshan-ul-hassan Usmani (Founder & Chief Data Scientist, PredictifyMe) explains.
on Oct 20, 2015 in Analysis, Data Candy, Data Visualization, Halloween, Trick-or-Treat
Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 20 and beyond
Easier Data Prep and Analysis for Data Scientists, Measure and Enhance Analytics Maturity, Amazon QuickSight, Textual Healing, and more.
on Oct 19, 2015 in Amazon QuickSight, Analytic Maturity, Data Preparation, Hadoop, RapidInsight
Harness Big Data with NTU part-time MSc
NTU part-time MSc Data Analytics for Business will give you the analytical and technical skills to maximize the big data revolution. Find out more at our open event on 11 Nov 2015.
on Oct 19, 2015 in MS in Analytics, Nottingham Trent University, UK
Which Movie Sequels Are Really Better? A Data Science Answer
The internet is filled with polls and lists of sequels that are better or worse movie in the series. Yet such rankings are often based on personal judgement and rarely on data and statistics. Here is our solution to analyze and visualize the movie series.
on Oct 19, 2015 in Data Analysis, Data Visualization, IMDb, James Bond, Movies, Silk.co
Rich Data Summit Takeaways
Data scientists get excited about algorithms. But nearly all time spent working with data involves acquiring, pipelining, annotating and cleaning it. At the Rich Data Summit in SF, data's dirty work took center stage.
on Oct 19, 2015 in CrowdFlower, Data Cleaning, Lukas Biewald, Nate Silver, Zachary Lipton
Big Data + Wrong Method = Big Fail
Big data is hyped as a gold mine, but Big Data applications are risky. Understand how to start with a minimum viable application and iterate to minimize the risk of failure.
on Oct 19, 2015 in Big Data, Big Data ROI, Challenges, Failure
The Beginners Guide to Predictive Workforce Analytics
Under increasing pressure and facing unique challenges, Human Resources departments are turning to analytics to improve their business practices. Learn what HR needs to be focused on, and what pitfalls they need to avoid.
on Oct 19, 2015 in Greta Roberts, HR, Workforce Analytics
Predictive Analytics Innovation Summit, Chicago, Nov 11-12
Join the industry leading analytics executives and learn from keynotes, workshops and panels sessions from dynamic organizations - save with code KD200 for one week only.
on Oct 19, 2015 in Chicago, IE Group, IL, Predictive Analytics, Summit
Top stories for Oct 11-17: R vs Python: head2head data analysis; Quora best advice: How to Learn Machine Learning
R vs Python: head to head data analysis; Best Advice From Quora: How to Learn Machine Learning; How Big Data Helps Build Smart Cities; Best Data Science Online Courses.
on Oct 18, 2015 in Top stories
AnalyticsVidhya Interview with Gregory Piatetsky-Shapiro, President KDnuggets
AnalyticsVidhya wide-ranging interview with Gregory Piatetsky-Shapiro - origins of KDnuggets, founding of KDD, Learning Data Science, R vs Python, the risks and benefits of AI, Analytics in India, and more.
on Oct 17, 2015 in About Gregory Piatetsky, AI, Analytics Vidhya, Kunal Jain
Big Data for Social Good: UC Berkeley and Geisinger Health Collider Project
The Geisinger Health Collider Project gives participating students first-hand experience with various techniques, ideas, and challenges stemming from clinical informatics by using real clinical data to address impactful problems in healthcare.
on Oct 17, 2015 in Big Data, Roberto Zicari, Social Good, UC Berkeley
DistrictDataLabs Courses on Data Mining, Machine Learning, R, NLP, Social Media, and more
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.
on Oct 17, 2015 in Arlington, Data Mining, District Data Labs, Django, Machine Learning, NLP, Python, R, Social Media Analytics, VA
Global Big Data Conference, Dallas, Nov 6-8
Learn emerging big data trends, developing new skills with hands on workshops, analyze industry case studies, learn emerging best practices in Big Data, Data Science, Machine Learning, and Predictive Analytics.
on Oct 16, 2015 in Dallas, Global Big Data Conference, TX
SFBayACM Silicon Valley Data Science Camp, Oct 24 2015
This is a great (almost free = $5) opportunity to learn about Data Science and connect with others. SF Bay ACM annual Data Science Camp combines keynote, optional tutorial, and sessions.
on Oct 16, 2015 in ACM, Apache Spark, Bootcamp, CA, Data Science, R, San Jose, SFbayACM
How Big Data Helps Build Smart Cities
Smart cities face serious challenges prior to widespread acceptance, but their integrated use of Big Data, IoT, and other technologies to solve contemporary urban issues should eventually lead to their adoption.
on Oct 16, 2015 in Big Data, IoT, RFID, Smart City, South Korea
The Best Advice From Quora on ‘How to Learn Machine Learning’
Top machine learning writers on Quora give their advice on learning machine learning, including specific resources, quotes, and personal insights, along with some extra nuggets of information.
on Oct 15, 2015 in Books, Machine Learning, Matthew Mayo, MOOC, Quora, Sean McClure, Xavier Amatriain
PAW: Impressive Line-up at Predictive Analytics World London
The leading vendor-neutral analytics conference, Predictive Analytics World London is packed with top predictive analytics experts, practitioners, authors and business thought leaders.
on Oct 15, 2015 in London, PAW, Predictive Analytics World, UK
Dell: The Great Analytics Migration – free e-book
If you want to switch to an analytics platform with more functionality and less cost, how to manage all the people, processes and technologies involved? We just wrote the e-book on it - after we moved hundreds of our employees to a new analytics solution.
on Oct 15, 2015 in Analytics, Dell, Free ebook, Migration
Do more with Python: Creating a graph application with Python, Neo4j, Gephi, and Linkurious
Here is how to build a neat app with graph visualization of Python and related topics from Packt and StackOverflow, combining Gephi, Linkurious, and Neo4j.
on Oct 14, 2015 in Gephi, Graph Visualization, Linkurious, Neo4j, Packt Publishing, Python, StackOverflow
Strata + Hadoop World, Singapore, Dec 1-3: 2 for 1 Passes
Register with code 2FOR1P and get a free pass of equal value to Strata + Hadoop World in Singapore. Expires Oct 31.
on Oct 13, 2015 in Hadoop, Singapore, Strata
Top KDnuggets tweets, Oct 6-12: Big innovations in Data Science yet to come; 5 steps to learn Data Science
Big innovations in #DataScience yet to come: new #algorithms, data, new thinking; 5 steps to learn #DataScience: 1. Learn to love data; Why Tracy-Widom Mysterious Statistical Law so common - Phase transitions; Best of /r/MachineLearning in September.
on Oct 13, 2015 in Data Science Education, Deep Learning, Innovation, R, Tracy-Widom
Big Data Bootcamp, Tampa, Dec 7-9, KDnuggets discount
This bootcamp is targeted to people who want to understand the emerging world of Big Data, covering Hadoop, Spark, IoT, Kafka, Real time streaming, Industry use cases, NoSQL, Data Science, R, Python, Machine Learning, and more.
on Oct 13, 2015 in Bootcamp, FL, Global Big Data Conference, Tampa
R vs Python: head to head data analysis
The epic battle between R vs Python goes on. Here we are comparing both of them in terms of generic tasks of data scientist’s like reading CSV, finding data summary, PCA, model building, plotting, and many more.
on Oct 13, 2015 in Data Visualization, Python, Python vs R, R, scikit-learn, Vik Paruchuri
Aspect Based Sentiment Analysis Competition
SemEval is back and so is the Aspect Based Sentiment Analysis (ABSA) competition, which has gone multilingual for ABSA16. Get all of the details below.
on Oct 13, 2015 in Competition, Sentiment Analysis
SMU MS in Data Science Online
Designed for working professionals, DataScience@SMU features live online face-to-face classes, hands-on, project-based coursework, collaborative peer network, and more.
on Oct 13, 2015 in Data Science Education, MS in Data Science, Online Education, SMU
Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 13 and beyond
Optimizing Data Lake, Data Mining: Failure to Launch, Easier Data Prep and Analysis for Data Scientists, and more.
on Oct 12, 2015 in Data Lakes, Data Preparation, Failure to Launch, RapidInsight, TMA
Northwestern MOOC Specialization: “Social Marketing – How to Profit in a Digital World;” Lexalytics CMO Seth Redmore Featured Faculty Member
Six-part series offered through Coursera will teach entrepreneurs, executives, and marketing professionals how to manage, measure, and monetize social media marketing programs.
on Oct 12, 2015 in Coursera, Lexalytics, Marketing, MOOC, Northwestern, Social Media
Best Data Science Online Courses
The number of online data science courses have exploded in recent years and there courses for any needs. Here is a extensive list of free and paid courses from Coursera, DataCamp, Dataquest, edX, Udacity, Udemy, and other major providers.
on Oct 12, 2015 in Brendan Martin, Coursera, Data Science Education, DataCamp, Dataquest, edX, O'Reilly, Online Education, Udacity, Udemy
OpenText Data Digest, Oct 9: Baseball Playoffs
We love our data the way we love our baseball—lots of visuals and power hitters that crush it over the wall for the walk-off win. Check out which visualizations made to top three bases for this week’s OpenText data visualization.
on Oct 12, 2015 in Baseball, Data Visualization, OpenText
Top stories for Oct 4-10: 5 steps to actually learn data science; 90+ Active Blogs on Analytics, Big Data, Data Mining
Top 5 arXiv Deep Learning Papers, Explained; 5 steps to actually learn data science; 90+ Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning; Does Deep Learning Come from the Devil?
on Oct 11, 2015 in Top stories
Big Data Bootcamp, Santa Clara, Nov 13-15
Fast paced, vendor agnostic, technical overview of the Big Data landscape targeted towards technical and business people who want to understand the emerging world of Big Data. Special KDnuggets discount.
on Oct 10, 2015 in Bootcamp, CA, Global Big Data Conference, Santa Clara
KDD Cup 2016 Call for Proposals
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2016 is being held in San Francisco, California, from August 13-17, 2016. KDD is currently inviting KDD Cup competition proposals at this time.
on Oct 10, 2015 in KDD, KDD Cup, KDD-2016
Five Principles for Applying Data Science for Social Good
Well-meaning data scientists often fail to reach their full potential when working for social good. The following 5 principles can help improve this situation.
on Oct 10, 2015 in DataKind, Jake Porway, Social Good
Big Data Analytics for Lenders and Creditors
Credit scoring means applying a statistical model to assign a risk score to a credit application or to an existing credit account. Here we are suggesting how data science and big data can help making the better sense of different risk factors and accurate predictions.
on Oct 9, 2015 in Big Data, Credit Risk, Goran Dragosavac
Does Deep Learning Come from the Devil?
Deep learning has revolutionized computer vision and natural language processing. Yet the mathematics explaining its success remains elusive. At the Yandex conference on machine learning prospects and applications, Vladimir Vapnik offered a critical perspective.
on Oct 9, 2015 in Berlin, Deep Learning, Machine Learning, Support Vector Machines, SVM, Vladimir Vapnik, Yandex, Zachary Lipton
ASA says Statistics is Foundational to Data Science
ASA cites statistics as one of three foundational communities in data science and emphasizes the importance of collaboration among all field’s key disciplines.
on Oct 9, 2015 in ASA, Data Science, Statistics
Where Should I Work In Big Data?
Unravelling the mystery of where to work as a data scientist, whether to venture into start-up or join a safe course of established vendors has been haunting many aspirants. Find out yourself by answer these five questions!
on Oct 9, 2015 in Big Data, Hiring, Matt Reaney, Startup
KDnuggets Milestone: 200,000 unique visitors
KDnuggets passes an important milestone - 200,000 unique visitors. How did we do it?
on Oct 8, 2015 in About KDnuggets
90+ Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning
Stay on top of your data science skills game! Here's a list of 90+ active blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.
on Oct 8, 2015 in Big Data, Blogs, Data Science, Deep Learning, Hadoop, Machine Learning
Top stories in September: 60+ Free Books on Big Data, Data Science; The one language a Data Scientist must master
60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning; The one language a Data Scientist must master; Top 20 Data Science MOOCs; 30 best Harvard Business Review articles on Big Data.
on Oct 8, 2015 in Top stories
Data Science Education: Where It Needs To Begin
Most data science education centers on graduate degrees, with only 14 US undergraduate analytics degrees in 2014. With the vast amounts of data being generated, should there be more data science education at the undergraduate level?
on Oct 8, 2015 in Big Data, Data Science Education, Data Scientist
The Data Science for Internet of Things – practitioner course
The Data Science for IoT is the world first course that helps you to become a Data Scientist for the Internet Of Things. Starts Nov 10 in London, UK or online.
on Oct 8, 2015 in Data Science, Internet of Things, IoT, London, Online Education, UK
Online course: Credit Risk Modeling
The course covers basic and advanced modeling, including stress testing Probability of Default (PD), Loss Given Default (LGD ) and Exposure At Default (EAD) models.
on Oct 7, 2015 in Bart Baesens, Credit Risk, Online Education, Risk Modeling
Recurrent Neural Networks Tutorial, Introduction
Recurrent Neural Networks (RNNs) are popular models that have shown great promise in NLP and many other Machine Learning tasks. Here is a much-needed guide to key RNN models and a few brilliant research papers.
on Oct 7, 2015 in Deep Learning, Neural Networks, NLP, Recurrent Neural Networks
How big data can help in home health care?
Proper home care services can reduce both the chances and the cost of hospitalization and manage illness. Understand what big data promises for the healthcare sector and what are practical hurdles standing between the current solutions.
on Oct 7, 2015 in Big Data, Healthcare, Kaushik Pal
Top KDnuggets tweets, Sep 29 – Oct 5: Top 5 arXiv Deep Learning Papers, Explained
Crushed it! Useful advice for landing a data science job; Top 5 arXiv Deep Learning Papers, Explained; 30 best HBR articles; Researcher who broke Netflix Prize to find if data is truly anonymized w. grant from Google.
on Oct 6, 2015 in Anonymity, arXiv, Deep Learning, R
Predictive Analytics World returns to London on 28-29 October
Predictive Analytics World is the leading cross-vendor event for predictive analytics professionals, managers, and practitioners, with concrete examples of deployed predictive analytics and case studies, expertise, and resources for bigger wins and broader capabilities.
on Oct 6, 2015 in Dean Abbott, John Elder, London, PAW, Predictive Analytics World, UK, Usama Fayyad
75+ upcoming October – May Meetings in Analytics, Big Data, Data Mining, Data Science
Coming soon: PAW Government, Rich Data Summit, Polyanalyst User Conf, PAW London, Crunch Budapest, IEEE Big Data, Big Data Techcon Chicago, EARL Boston, PAW Berlin, and many more.
on Oct 6, 2015 in Boston, CA, Chicago, France, IL, London, MA, San Francisco, UK, USA
5 steps to actually learn data science
Data science is a broad and varied field, and hence the path to becoming a unicorn is full of darkness. To light up your path and guide you to become one, here are 5 simple steps to be followed.
on Oct 6, 2015 in Data Science, Data Science Education, Vik Paruchuri
Self-Paced E-learning course: Advanced Analytics in a Big Data World
The course covers the entire analytics process, from data preprocessing to advanced modeling, including ensemble methods (bagging, boosting, random forests), neural networks, SVMs, Bayesian networks, social networks, monitoring and more.
on Oct 6, 2015 in Advanced Analytics, Bart Baesens, Big Data, Online Education
OpenText Data Digest Oct 2: Traffic and Public Transit
Despite constant congestion, data scientists are always coming up with ways to analyze traffic patterns to ensure you get to your desk by 9 a.m. Whether your transportation is trains or cars, we’ve got you covered, this week.
on Oct 6, 2015 in Data Visualization, OpenText, Traffic
Top /r/MachineLearning Posts, September: Implement a neural network from scratch in C++
Neural network in C++ for beginners, Chinese character handwriting recognition beats humans, a handy machine learning algorithm cheat sheet, neural nets versus functional programming, and a neural nets paper repository.
on Oct 6, 2015 in C++, Deep Learning, Matthew Mayo, Neural Networks, Python, R, Reddit
Easier Data Prep and Analysis for Data Scientists, Oct 20 Webinar
Rapid Insight will show tools that make the data preparation and analysis process significantly faster, without losing the flexibility of advanced programming or SQL tools.
on Oct 6, 2015 in Data Preparation, RapidInsight, SQL
INFORMS Courses: Essential Practice Skills, Data Exploration and Visualization, November, Baltimore
Two INFORMS courses teach Essential Practice Skills for High-Impact Analytics Projects (Nov 18-19) and Data Exploration & Visualization (Nov 10-11). Both courses are given at Johns Hopkins University, Baltimore, MD.
on Oct 5, 2015 in Baltimore, Best Practices, Data Exploration, Data Visualization, Freakalytics, INFORMS, MD, Skills
Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 6 and beyond
Upcoming Webcasts on Analytics, Big Data, Data Science - Oct 6 and beyond, Preventing a Big Data Letdown, Compensation of Predictive Analytics Professionals, Predictive Workforce Playbook, Fraud Detection, Optimizing the Data Lake, and more.
on Oct 5, 2015 in Data Lakes, Fraud Detection, Salary, Workforce Analytics
Top stories for Sep 27 – Oct 3: Top 5 arXiv Deep Learning Papers, Explained; 30 best HBR articles on Big Data, Data Science
Top 5 arXiv Deep Learning Papers, Explained; 30 Can't miss Harvard Business Review articles on Data Science, Big Data and Analytics; Data Lake vs Data Warehouse: Key Differences.
on Oct 4, 2015 in Top stories
HeroX Integra Gold Rush Data Science Challenge
The Integra Gold Rush Challenge invites people from around the world, from any background to analyze this data and win prizes totaling CAD $1 million.
on Oct 3, 2015 in Canada, Challenge, Gold, HeroX
Don’t Let Data Silos and Dark Data Clog Your Data Supply Chain
With the rise of the big data, it has been cheaper and easier to accumulate the huge amount of data. But make sure you are getting value out of this data, otherwise it could create a bottleneck and get redundant for the business.
on Oct 3, 2015 in Attivio, Business Intelligence, Data Silos, Forrester, Supply Chain
September Academic Positions in Business Analytics, Data Mining, Data Science, Machine Learning
Postdoc at Vanderbilt and Uni. Passau, Research Associates at Aalto and Johannes Gutenberg U, Researchers in Singapore, Faculty at USFCA and Syracuse, and more.
on Oct 2, 2015 in Finland, Germany, Singapore, Syracuse University, University of Hawaii, University of San Francisco, Vanderbilt
OpenText Data Digest Sep 25: US Maps
This week’s Data Driven Digest focuses on three maps of the United States that are distinct more because of the behaviors of the people that live in them than the actual lines that separate them.
on Oct 2, 2015 in Data Visualization, Maps, OpenText, USA
Data science job market – what it’s like
Data scientist interviews can be complex and there is no definite recipe for the success. Understand the complications and processes of an interview and what you should be careful about before accepting the offer.
on Oct 2, 2015 in Data Science Skills, Data Scientist, Hiring, Skills, Trey Causey
Crushed it! Landing a data science job
Data scientist interviews depend on the company and the team, it might look like a software developer’s interview, or statistician’s interview. Here we collected some hot tips to pass along if you’re thinking about a move soon.
on Oct 1, 2015 in Data Scientist, Erin Shellman, Hiring, Interview
Top 5 arXiv Deep Learning Papers, Explained
Top deep learning papers on arXiv are presented, summarized, and explained with the help of a leading researcher in the field.
on Oct 1, 2015 in arXiv, Deep Learning, Explained, Hugo Larochelle
NYU Stern Master of Science in Business Analytics
The NYU Stern MS in Business Analytics teaches experienced professionals how to understand the role of evidence-based data in decision-making and to leverage data as a valuable and predictive strategic asset. Upcoming application deadline is Nov 15.
on Oct 1, 2015 in MS in Business Analytics, New York City, NY, NYU
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