All (105) | Courses, Education (17) | Meetings (8) | News, Features (19) | Opinions, Interviews, Reports (30) | Publications (7) | Software (2) | Top Tweets (4) | Tutorials, Overviews, How-Tos (11) | Webcasts (7)
- Data Natives 2015: A Conference for the Data-Driven Generation, Berlin, Nov 19-20 - Oct 30, 2015.
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.
- How Big Data is used in Recommendation Systems to change our lives - Oct 30, 2015.
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.
- October Academic Positions in Analytics, Data Mining, Data Science, Machine Learning - Oct 30, 2015.
Academic and research positions at PNNL, U. of Arizona, UCSC, Eastern Michigan University, Florida Institute of Technology, USF CA, UIC, and U. of Iowa.
- Integrating Python and R, Part 2: Executing R from Python and Vice Versa - Oct 30, 2015.
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.
- A Neural Network in 11 lines of Python - Oct 30, 2015.
A bare bones neural network implementation to describe the inner workings of back-propagation.
- The Human Element of Data Science - Oct 29, 2015.
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.
- Integrating Python and R into a Data Analysis Pipeline, Part 1 - Oct 29, 2015.
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.
- We need a statistically rigorous and scientifically meaningful definition of replication - Oct 29, 2015.
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.
- Data Science of IoT: Sensor fusion and Kalman filters, Part 1 - Oct 29, 2015.
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.
- An Inside View of Language Technologies at Google - Oct 29, 2015.
Learn about language technologies at Google, including projects, technologies, and philosophy, from an interview with a Googler.
- SAS Adds Certifications for Big Data and Data Science - Oct 28, 2015.
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.
- Deep Learning Finds What Makes a Good #selfie - Oct 28, 2015.
Ever wonder how a convolutional neural network would rate your selfies? Well, wonder no more!
- Explaining Analytics to Decision Makers: Insights to Actions - Oct 27, 2015.
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.
- Top KDnuggets tweets, Oct 20-26: Why Self-Driving Cars Must Be Able to Kill: an impossible dilemma of algorithmic morality - Oct 27, 2015.
Why Self-Driving Cars Must Be Able to Kill: an impossible dilemma of algorithmic morality; Cartoon: KDnuggets Addiction; Good overview: #BigData Infrastructure at IFTTT.
- 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?
- Saint Mary’s Mathematically Rigorous MS in Data Science, Primarily Online - Oct 27, 2015.
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.
- Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 27 and beyond - Oct 26, 2015.
Amazon QuickSight, Textual Healing, What's new in Statistica 13, Real-time Hadoop and IoT, Ad Hoc Visual Discovery, and more.
- You’ve Read the Book, Now Listen to the Podcast - Oct 26, 2015.
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.
- OpenText Data Digest Oct 23: World Statistics Day - Oct 26, 2015.
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.
- Introducing: Blocks and Fuel – Frameworks for Deep Learning in Python - Oct 26, 2015.
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.
- Random vs Pseudo-random – How to Tell the Difference - Oct 26, 2015.
Statistical know-how is an integral part of Data Science. Explore randomness vs. pseudo-randomness in this explanatory post with examples.
- Top stories for Oct 18-24: R vs Python: head to head data analysis; Big Data + Wrong Method = Big Fail - Oct 25, 2015.
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.
- Cartoon: KDnuggets Addiction - Oct 24, 2015.
New Cartoon looks at a serious case of KDnuggets addiction and what can be done about it.
- New Books on Accelerating Discovery, Event Mining, Networking for Big Data - Oct 23, 2015.
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%.
- How to Use Data Visualizations to Win Over Your Audience - Oct 22, 2015.
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.
- Data Science Programming: Python vs R - Oct 22, 2015.
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.
- The Data Science Machine, or ‘How To Engineer Feature Engineering’ - Oct 22, 2015.
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?
- Unlock the Power of Spark with IBM Watson and Twitter - Oct 22, 2015.
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.
- There is a new Statistica in town – Oct 29 Webinar - Oct 22, 2015.
Dell unveils all the cool, new features in Statistica 13 in Oct 29 webinar - reserve your place.
- Spark + SETI: Amping up Spark SQL with Parquets - Oct 21, 2015.
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.
- OpenText Data Digest, Oct 16: Millennial Parenting - Oct 21, 2015.
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.
- 2015 Updated Analytics Compensation and Demographics - Oct 21, 2015.
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.
- Top KDnuggets tweets, Oct 13-19: R vs Python: head to head; Machine Learning for Developers tutorial - Oct 20, 2015.
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.
- MetaMind Mastermind Richard Socher: Uncut Interview - Oct 20, 2015.
In a wide-ranging interview, Richard Socher opens up about MetaMind, deep learning, the nature of corporate research, and the future of machine learning.
- RE.WORK Connect: Shaping a Hyper-connected World - Oct 20, 2015.
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.
- TMA Predictive Analytics Data Mining Training [San Jose, Dec 7-11] - Oct 20, 2015.
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.
- New Poll: Should Data Science Include Ethics Training? - Oct 20, 2015.
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.
- Infographic – Data Scientist or Business Analyst? Knowing the Difference is Key - Oct 20, 2015.
Infographic depicting unique differences between data scientists and business analysts. Find out what type of professional is needed to meet your organization’s needs.
- Lavastorm – 5 Tips to Get More From Tableau - Oct 20, 2015.
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.
- Lets talk about Ethics in Analytics / Data Science - Oct 20, 2015.
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.
- Trick-or-Treat a Data Scientist - Oct 20, 2015.
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.
- Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 20 and beyond - Oct 19, 2015.
Easier Data Prep and Analysis for Data Scientists, Measure and Enhance Analytics Maturity, Amazon QuickSight, Textual Healing, and more.
- Harness Big Data with NTU part-time MSc - Oct 19, 2015.
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.
- Which Movie Sequels Are Really Better? A Data Science Answer - Oct 19, 2015.
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.
- Rich Data Summit Takeaways - Oct 19, 2015.
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.
- Big Data + Wrong Method = Big Fail - Oct 19, 2015.
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.
- The Beginners Guide to Predictive Workforce Analytics - Oct 19, 2015.
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.
- Predictive Analytics Innovation Summit, Chicago, Nov 11-12 - Oct 19, 2015.
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.
- Top stories for Oct 11-17: R vs Python: head2head data analysis; Quora best advice: How to Learn Machine Learning - Oct 18, 2015.
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.
- AnalyticsVidhya Interview with Gregory Piatetsky-Shapiro, President KDnuggets - Oct 17, 2015.
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.
- Big Data for Social Good: UC Berkeley and Geisinger Health Collider Project - Oct 17, 2015.
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.
- 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.
- Global Big Data Conference, Dallas, Nov 6-8 - Oct 16, 2015.
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.
- SFBayACM Silicon Valley Data Science Camp, Oct 24 2015 - Oct 16, 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.
- How Big Data Helps Build Smart Cities - Oct 16, 2015.
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.
- The Best Advice From Quora on ‘How to Learn Machine Learning’ - Oct 15, 2015.
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.
- PAW: Impressive Line-up at Predictive Analytics World London - Oct 15, 2015.
The leading vendor-neutral analytics conference, Predictive Analytics World London is packed with top predictive analytics experts, practitioners, authors and business thought leaders.
- Dell: The Great Analytics Migration – free e-book - Oct 15, 2015.
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.
- Do more with Python: Creating a graph application with Python, Neo4j, Gephi, and Linkurious - Oct 14, 2015.
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.
- Strata + Hadoop World, Singapore, Dec 1-3: 2 for 1 Passes - Oct 13, 2015.
Register with code 2FOR1P and get a free pass of equal value to Strata + Hadoop World in Singapore. Expires Oct 31.
- Top KDnuggets tweets, Oct 6-12: Big innovations in Data Science yet to come; 5 steps to learn Data Science - Oct 13, 2015.
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.
- Big Data Bootcamp, Tampa, Dec 7-9, KDnuggets discount - Oct 13, 2015.
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.
- R vs Python: head to head data analysis - Oct 13, 2015.
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.
- Aspect Based Sentiment Analysis Competition - Oct 13, 2015.
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.
- SMU MS in Data Science Online - Oct 13, 2015.
Designed for working professionals, DataScience@SMU features live online face-to-face classes, hands-on, project-based coursework, collaborative peer network, and more.
- Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 13 and beyond - Oct 12, 2015.
Optimizing Data Lake, Data Mining: Failure to Launch, Easier Data Prep and Analysis for Data Scientists, and more.
- Northwestern MOOC Specialization: “Social Marketing – How to Profit in a Digital World;” Lexalytics CMO Seth Redmore Featured Faculty Member - Oct 12, 2015.
Six-part series offered through Coursera will teach entrepreneurs, executives, and marketing professionals how to manage, measure, and monetize social media marketing programs.
- Best Data Science Online Courses - Oct 12, 2015.
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.
- OpenText Data Digest, Oct 9: Baseball Playoffs - Oct 12, 2015.
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.
- Top stories for Oct 4-10: 5 steps to actually learn data science; 90+ Active Blogs on Analytics, Big Data, Data Mining - Oct 11, 2015.
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?
- Big Data Bootcamp, Santa Clara, Nov 13-15 - Oct 10, 2015.
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.
- KDD Cup 2016 Call for Proposals - Oct 10, 2015.
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.
- Five Principles for Applying Data Science for Social Good - Oct 10, 2015.
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.
- Big Data Analytics for Lenders and Creditors - Oct 9, 2015.
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.
- Does Deep Learning Come from the Devil? - Oct 9, 2015.
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.
- ASA says Statistics is Foundational to Data Science - Oct 9, 2015.
ASA cites statistics as one of three foundational communities in data science and emphasizes the importance of collaboration among all field’s key disciplines.
- Where Should I Work In Big Data? - Oct 9, 2015.
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!
- KDnuggets Milestone: 200,000 unique visitors - Oct 8, 2015.
KDnuggets passes an important milestone - 200,000 unique visitors. How did we do it?
- 90+ Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning - Oct 8, 2015.
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.
- Top stories in September: 60+ Free Books on Big Data, Data Science; The one language a Data Scientist must master - Oct 8, 2015.
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.
- Data Science Education: Where It Needs To Begin - Oct 8, 2015.
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?
- The Data Science for Internet of Things – practitioner course - Oct 8, 2015.
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.
- Online course: Credit Risk Modeling - Oct 7, 2015.
The course covers basic and advanced modeling, including stress testing Probability of Default (PD), Loss Given Default (LGD ) and Exposure At Default (EAD) models.
- Recurrent Neural Networks Tutorial, Introduction - Oct 7, 2015.
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.
- How big data can help in home health care? - Oct 7, 2015.
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.
- Top KDnuggets tweets, Sep 29 – Oct 5: Top 5 arXiv Deep Learning Papers, Explained - Oct 6, 2015.
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.
- Predictive Analytics World returns to London on 28-29 October - Oct 6, 2015.
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.
- 75+ upcoming October – May Meetings in Analytics, Big Data, Data Mining, Data Science - Oct 6, 2015.
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.
- 5 steps to actually learn data science - Oct 6, 2015.
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.
- Self-Paced E-learning course: Advanced Analytics in a Big Data World - Oct 6, 2015.
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.
- OpenText Data Digest Oct 2: Traffic and Public Transit - Oct 6, 2015.
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.
- Top /r/MachineLearning Posts, September: Implement a neural network from scratch in C++ - Oct 6, 2015.
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.
- Easier Data Prep and Analysis for Data Scientists, Oct 20 Webinar - Oct 6, 2015.
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.
- INFORMS Courses: Essential Practice Skills, Data Exploration and Visualization, November, Baltimore - Oct 5, 2015.
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.
- Upcoming Webcasts on Analytics, Big Data, Data Science – Oct 6 and beyond - Oct 5, 2015.
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.
- Top stories for Sep 27 – Oct 3: Top 5 arXiv Deep Learning Papers, Explained; 30 best HBR articles on Big Data, Data Science - Oct 4, 2015.
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.
- HeroX Integra Gold Rush Data Science Challenge - Oct 3, 2015.
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.
- Don’t Let Data Silos and Dark Data Clog Your Data Supply Chain - Oct 3, 2015.
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.
- September Academic Positions in Business Analytics, Data Mining, Data Science, Machine Learning - Oct 2, 2015.
Postdoc at Vanderbilt and Uni. Passau, Research Associates at Aalto and Johannes Gutenberg U, Researchers in Singapore, Faculty at USFCA and Syracuse, and more.
- OpenText Data Digest Sep 25: US Maps - Oct 2, 2015.
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.
- Data science job market – what it’s like - Oct 2, 2015.
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.
- Crushed it! Landing a data science job - Oct 1, 2015.
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.
- Top 5 arXiv Deep Learning Papers, Explained - Oct 1, 2015.
Top deep learning papers on arXiv are presented, summarized, and explained with the help of a leading researcher in the field.
- NYU Stern Master of Science in Business Analytics - Oct 1, 2015.
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.