Topics: 
Aug
2016 Sep
All (104) | Courses, Education (13) | Meetings (18) | News, Features (23) | Opinions, Interviews (19) | Software (8) | Tutorials, Overviews (20) | Webcasts & Webinars (3)
- Webinar: The Role of Text Mining in Patent Research, Oct 6
- Sep 30, 2016.
Learn how Dr. Thorsten Schweikardt developed a patent analysis workflow, making a previously difficult task achievable by using text mining.
- Embedded Analytics: The Future of Business Intelligence
- Sep 30, 2016.
An overview of the evolution of Business Intelligence, and some insight into where its future lie: embedded analytics.
- Predicting Future Human Behavior with Deep Learning
- Sep 30, 2016.
Carl Vondrick, MIT researcher, who studies computer vision and machine learning, discusses how to use Big Data with minimal annotations and applications to predictive vision and scene understanding.
- Mining Massive Datasets, free Stanford online course, starts Oct 11
- Sep 29, 2016.
Top researchers Leskovec, Anand, and Ullman teach online course on Mining of Massive Datasets. The course is free and starts on Stanford platform Oct 11, 2016.
- Deep Learning Reading Group: SqueezeNet
- Sep 29, 2016.
This paper introduces a small CNN architecture called “SqueezeNet” that achieves AlexNet-level accuracy on ImageNet with 50x fewer parameters.
- Data Science of Sales Calls: The Surprising Words That Signal Trouble or Success
- Sep 29, 2016.
While not as profound a problem as uncovering the secrets of the universe, how to conduct a successful sales conversation is an age-old problem, impacting millions of people every day.
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Top Data Scientist Claudia Perlich on Biggest Issues in Data Science
- Sep 29, 2016.
Find out what top data scientist Claudia Perlich believes are - and are not - the biggest issues in data science today, and why spending 80% of their time with data preparation is not a problem. - Online Master of Science in Predictive Analytics
- Sep 29, 2016.
Build hot skills for the growing analytics field, learn key statistical concepts and practical applications from distinguished Northwestern faculty and industry experts and prepare for leadership level career. Winter application deadline Oct 15.
- Top KDnuggets tweets, Sep 21-27: What is the #Blockchain and Why is it So Important? Watch #StrataHadoop #NYC Keynotes Live Sep 28-29
- Sep 28, 2016.
Top #DataScientists to follow on Twitter: @geoff_hinton @ylecun @SebastianThrun; What is the #Blockchain and Why is it So Important? The (Not So) New Data Scientist Venn Diagram; 9 Key #DeepLearning Papers, Explained.
- Information Spectrum of Diffusion – What Analysts Need to Know
- Sep 28, 2016.
Quandl, which is a source of financial, economic, and alternative data, created a graphic called The Spectrum of Diffusion, describing the stages of information diffusion (accessibility) from "untapped" to "fully commoditized."
- Call for bids to host KDD-2019, Premier Research Conference on Data Science and Data Mining
- Sep 28, 2016.
ACM SIGKDD Executive Committee hereby invites proposals to host the annual KDD Conference in 2019. The conference should take place in August 2019.
- Deep Learning Singapore & Machine Intelligence NYC – KDnuggets Offer
- Sep 28, 2016.
Explore the latest machine learning research, technology and applications, with 2 RE.WORK events: the Deep Learning Summit in Singapore (20-21 Oct) and the Machine Intelligence Summit in New York City (Nov 2-3). Use code KDNUGGETS for 20% off.
- 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.
- Brainwaves hackathon on Machine Learning
- Sep 28, 2016.
This hackathon aims at attracting top developers for a 30-hour build session focused on Machine Learning. The first qualifying event will be held online in October.
- Why Not So Hadoop?
- Sep 27, 2016.
Are Big Data and Hadoop synonymous? Not really, but they are often conflated. Has Hadoop lived up to its hype? In this article, we will look at a brief history of Hadoop and see where it stands today.
- Cognitive and Data Sciences Education Workshop, Las Vegas, Oct 23
- Sep 27, 2016.
Evolving Education with Cognitive and Data Sciences brings together faculty, academic and industry leaders to explore how to rapidly evolve academic and research programs to satisfy the exploding demand for graduates skilled in cognitive and data sciences. Register today!
- Top Data Scientist Claudia Perlich’s Favorite Machine Learning Algorithm
- Sep 27, 2016.
Interested in the reasons why a top data scientist is partial to one particular algorithm over others? Read on to find out.
- Insights From Data Science Giants ahead of PAW NYC, Oct 23-27
- Sep 27, 2016.
PAW for Business, PAW Financial and PAW Healthcare will take place in NYC, Oct 23-27, Get early insight from the presenters from these in-depth interviews, and use code KDNPAW150 to save.
- Big Data Masters Course to Transform Your Career
- Sep 27, 2016.
The Simplilearn Online Masters Program ensures that you transform into a Hadoop Architect by acquiring core skill sets, including Hadoop Development, Real time processing using Spark, and NoSQL database technology. Learn more.
- The Trump Phenomenon: A Twitter Based Recount
- Sep 26, 2016.
This analysis uses Twitter data to perform a sentiment analysis to help determine how people truly feel about Trump. We found that while his fans have supported him throughout his entire campaign, more and more Twitter users have started to grow tired of Trump’s attitude.
- O’Reilly Live Training–Real-time. Real experts. Real learning.
- Sep 26, 2016.
Get intensive, hands-on training from O'Reilly's expert network on critical data topics - from SQL fundamentals to distributed computing; enterprise strategy to data science at scale.
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Data Science for Internet of Things (IoT): Ten Differences From Traditional Data Science
- Sep 26, 2016.
The connected devices (The Internet of Things) generate more than 2.5 quintillion bytes of data daily. All this data will significantly impact business processes and the Data Science for IoT will take increasingly central role. Here we outline 10 main differences between Data Science for IoT and traditional Data Science. - Comparing Clustering Techniques: A Concise Technical Overview
- Sep 26, 2016.
A wide array of clustering techniques are in use today. Given the widespread use of clustering in everyday data mining, this post provides a concise technical overview of 2 such exemplar techniques.
- Neural Designer: Predictive Analytics Software
- Sep 26, 2016.
Neural Designer advanced neural network algorithms, combined with a simple user interface and fast performance, make it a great tool for data scientists. Download free 15-day trial version.
- Advancing Analytics Conference, Melbourne, Australia, 6 October – Don’t Miss Out
- Sep 25, 2016.
Big data, AI, predictive analytics, business transformation… for all things analytics, join us on 6 Oct 2016 to hear from leading thinkers at the 2016 IAPA Australian National Conference, Advancing Analytics. Book your ticket today.
- Top Stories, Sep 18-24: Top Algorithms and Methods Used by Data Scientists; 9 Key Deep Learning Papers, Explained
- Sep 25, 2016.
Also - the 10 Algorithms Machine Learning Engineers Need to Know; Learning From Data (Intro Machine Learning) Caltech course starts on edX.
- Up to Speed on Deep Learning: August Update, Part 2
- Sep 23, 2016.
This is the second part of an overview of deep learning stories that made news in August. Look to see if you have missed anything.
- Top 16 Active Big Data, Data Science Leaders on LinkedIn
- Sep 23, 2016.
Who are the most active Big Data, Data Science Influencers and Leaders on LinkedIn? We analyze the data and bring you the list of key people to follow.
- Spark for Scale: Machine Learning for Big Data
- Sep 23, 2016.
This post discusses the fundamental concepts for working with big data using distributed computing, and introduces the tools you need to build machine learning models.
- Deep Learning Reading Group: Deep Residual Learning for Image Recognition
- Sep 22, 2016.
Published in 2015, today's paper offers a new architecture for Convolution Networks, one which has since become a staple in neural network implementation. Read all about it here.
- NIJ Crime Forecasting Challenge – help improve policing and public safety with data science!
- Sep 22, 2016.
The nation needs brilliant, creative minds to lead the next generation of crime forecasting. Enter the competition sponsored by National Institute of Justice to help improve policing and public safety with data science. $1.2 Million will be awarded.
- Data Science Basics: 3 Insights for Beginners
- Sep 22, 2016.
For data science beginners, 3 elementary issues are given overview treatment: supervised vs. unsupervised learning, decision tree pruning, and training vs. testing datasets.
- Top KDnuggets tweets, Sep 14-20: Why we need #DataScience: brain wont let us see 12 black dots at intersection
- Sep 21, 2016.
Why we need #DataScience: brain won't let us see 12 black dots at intersections; #Blurring sensitive info no longer safe! #MachineLearning can recover originals ;Pokemon Go Data; The #NeuralNetwork Zoo - Great chart of different configurations.
- Up to Speed on Deep Learning: August Update
- Sep 21, 2016.
Check out this thorough roundup of deep learning stories that made news in August, and see if there are any items of note that you missed.
- Support Vector Machines: A Concise Technical Overview
- Sep 21, 2016.
Support Vector Machines remain a popular and time-tested classification algorithm. This post provides a high-level concise technical overview of their functionality.
- KDnuggets Top Bloggers in August – Gold and Silver badges
- Sep 20, 2016.
We recognize KDnuggets Best Bloggers who had the most popular or most shared posts in August 2016. KDnuggets publishes over 100 blogs a month and standing out in such competition is non-trivial.
- Why people love PAW
- Sep 20, 2016.
Reading a case study doesn't compare to hearing from its author, and asking questions. Tutorials aren't the same as live walkthroughs. And networking is more personal. That's why people keep coming back to Predictive Analytics World. Use KDN150 to save.
- 9 Key Deep Learning Papers, Explained
- Sep 20, 2016.
If you are interested in understanding the current state of deep learning, this post outlines and thoroughly summarizes 9 of the most influential contemporary papers in the field.
- Learn to collect, classify, analyze, and model data
- Sep 20, 2016.
The courses offered in the Penn State World Campus 30-credit online Master's in Data Analytics degree could enhance your credentials in the growing field of data analytics.
- The Great Algorithm Tutorial Roundup
- Sep 20, 2016.
This is a collection of tutorials relating to the results of the recent KDnuggets algorithms poll. If you are interested in learning or brushing up on the most used algorithms, as per our readers, look here for suggestions on doing so!
- NYC Taxi Hackathon – find privacy risks in public taxi datasets
- Sep 19, 2016.
The NYC TLC has been a pioneer in sharing big data since 2010, but earlier data releases have been de-anonymized. TLC is considering releasing taxi data again, subject to a new anonymization method. This hackathon is to help test it.
- Machine Learning in a Year: From Total Noob to Effective Practitioner
- Sep 19, 2016.
Read how the author went from self-described total machine learning noob to being able to effectively use machine learning effectively on real world projects at work... all within a year.
- Random Forest®: A Criminal Tutorial
- Sep 19, 2016.
Get an overview of Random Forest here, one of the most used algorithms by KDnuggets readers according to a recent poll.
- Chief Data Scientist Forum, San Francisco, Nov 16-17
- Sep 19, 2016.
Learn what does it really mean to be a Chief Data Scientist, what strategies will lead you to success, how to identify and meet real business needs, the path to establishing a truly data-centric culture, and more. Get 10% off with code KDCDS.
- Top Stories, Sep 12-18: Top Algorithms Used by Data Scientists; 7 Steps to Mastering Apache Spark 2.0
- Sep 19, 2016.
Top Algorithms Used by Data Scientists; 7 Steps to Mastering Apache Spark 2.0; The (Not So) New Data Scientist Venn Diagram; Behind the Dream of Data Work as it Could Be; The Deception of Supervised Learning
- New sequence learning data set
- Sep 17, 2016.
A new data set for the study of sequence learning algorithms is available as of today. The data set consists of pen stroke sequences that represent handwritten digits, and was created based on the MNIST handwritten digit data set.
- Learning From Data (Introductory Machine Learning) Caltech course starts on edX Sep 18
- Sep 17, 2016.
This introductory Machine Learning course taught by top Caltech professor Abu-Mostafa covers theory, algorithms and applications, with focus on real understanding. Starts Sep 18, 2016 on edX.
- 7 Ways How Data Science Fuels The FinTech Revolution
- Sep 16, 2016.
Here are 7 ways how data science is at the core of the current transformation of the financial sector.
- 7 Steps to Mastering Apache Spark 2.0
- Sep 16, 2016.
Looking for a comprehensive guide on going from zero to Apache Spark hero in steps? Look no further! Written by our friends at Databricks, this exclusive guide provides a solid foundation for those looking to master Apache Spark 2.0.
- Microsoft Machine Learning Competition – Improve Women Health
- Sep 16, 2016.
Enter Microsoft Women Health Risk Assessment competition, develop machine learning solutions to accurately categorize young women for their particular health risk. Enter now - submissions due Sep 30.
- How top companies use data to make wise decisions
- Sep 15, 2016.
Lucky people are those who pay attention to patterns and maintain a healthy curiosity. Download JMP Foreword magazine and read about those people.
- Deep Learning Reading Group: Deep Compression
- Sep 15, 2016.
An concise overview of a paper covering three methods of compressing a neural network in order to reduce the size of the network on disk, improve performance, and decrease run time.
- Meet Data Science graduates – Metis Career Day Sep 22, San Francisco
- Sep 15, 2016.
During a 12-week intensive program, Metis data science students build five projects using machine learning and statistical modeling techniques in Python, industry-level visualizations in D3, and real-world data in cloud-based SQL, no-SQL, and Hadoop databases.
- Decision Trees: A Disastrous Tutorial
- Sep 15, 2016.
Get a concise overview of decision trees here, one of the most used KDnuggets reader algorithms as measured in a recent poll.
- 2 must-have tools for blazing fast Python performance
- Sep 15, 2016.
Intel has two must-have, highly optimized tools to help you get faster performance out of the box - with the least amount of effort.
- Advancing Analytics Conference, Melbourne, Australia, 6 October – New Speakers
- Sep 15, 2016.
The 2016 IAPA Australian National Conference, Advancing Analytics on 6 October, helps you to get up-to-speed with global advances and experiences from the brightest analytics minds globally and locally. Book your ticket today.
- Top KDnuggets tweets, Sep 07-13: Dask for #Parallel Programming; Computationally generated Average Face
- Sep 14, 2016.
Computationally generated Average Face; Dask for #Parallel Programming; The (Not So) New #DataScientist Venn Diagram; Human in #AI loop - #DeepLearning lets you take an image of a dress and show...
- SlangSD: A Sentiment Dictionary for Slang Words
- Sep 14, 2016.
The Slang Sentiment Dictionary (SlangSD) includes over 90,000 slang words together with their sentiment scores, facilitating sentiment analysis in user-generated contents.
- Data Scientist Pay and Location: Indeed’s Tech Salary Report Overview
- Sep 14, 2016.
An overview of Indeed.com's 2016 Tech Salary Report, and summary details of top cities for data-centric professions vis-a-vis adjusted salary.
- Big Data Bootcamp, Tampa, Dec 9-11
- Sep 14, 2016.
Global Big Data Conference is offering 3 day extensive Bootcamp on Big Data on Dec 9-11, 2016 in Tampa. This is a fast paced, vendor agnostic, technical overview of the Big Data landscape.
- Driving Data Science Productivity Without Compromising Quality
- Sep 14, 2016.
How will data science teams maintain quality standards in the face of advancing automation? Attend the IBM DataFirst Launch Event on Sep 27 in NYC and learn how to drive greater productivity from your data science teams without compromising the quality of the mission-critical business assets they produce.
- Predictive Analytics.
Max Results. Min Time. - Sep 13, 2016.Successful analytics in the big data era does not start with data and software. It starts with immersive hands-on training, and goal-driven strategy. Get this training with TMA courseware, which spans all skill levels and analytic team roles - Wash-DC in October or Live Online in November. - Behind the Dream of Data Work as it Could Be
- Sep 13, 2016.
This post is an insider's overview of data.world, and their attempt to build the most meaningful, collaborative, and abundant data resource in the world.
- Regis University MS in Data Science Program – Be the Difference Behind the Data
- Sep 13, 2016.
Through Regis project-based graduate program, you will get an ethical approach to data science, helping businesses untangle the complexities of data collection and analytics to build a better business and a more equitable society. Now that's a beautiful thing.
- The Deception of Supervised Learning
- Sep 13, 2016.
Do models or offline datasets ever really tell us what to do? Most application of supervised learning is predicated on this deception.
- INFORMS New Associate CAP Certification
- Sep 13, 2016.
Standing out in the crowd: New Associate CAP Certification enables employers to easily identify top young analytics talent.
- Big Data Bootcamp, Atlanta, Oct 7-9
- Sep 13, 2016.
Global Big Data Conference is offering 3 day extensive Bootcamp on Big Data on Oct 7 to Oct 9, 2016 in Atlanta. This is a fast paced, vendor agnostic, technical overview of the Big Data landscape.
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Top Algorithms and Methods Used by Data Scientists
- Sep 12, 2016.
Latest KDnuggets poll identifies the list of top algorithms actually used by Data Scientists, finds surprises including the most academic and most industry-oriented algorithms. - Big Data and The Internet of Things: A Match Made in Heaven
- Sep 12, 2016.
Think of data as the fuel that helps the Internet of Things run. Big data and the IoT basically go hand in hand -- a match made in heaven, so to speak.
- Evolving Education with Cognitive and Data Science, Oct 23
- Sep 12, 2016.
Evolving Education with Cognitive and Data Sciences brings together faculty, academic and industry leaders to explore how to rapidly evolve academic programs and research to satisfy the exploding demand for graduates skilled in cognitive and data sciences. Register today!
- Top Stories, Sep 5-11: Beginners Guide To Convolutional Neural Networks; Big Data Dilemma: Save Money or Make Money
- Sep 12, 2016.
Beginners Guide To Convolutional Neural Networks; Big Data Dilemma: Save Me Money Versus Make Me Money; The 10 Algorithms Machine Learning Engineers Need to Know; How to Become a Data Scientist
- Webinar: Breaking Data Science Open, Sep 15
- Sep 12, 2016.
Learn how to drive collaboration and data science teamwork; how to mitigate legal risk through open source assurance and appropriate package selection, and how to democratize innovation through broad access to open data science tools.
- Big Data Bootcamp, Denver, Sep 30-Oct 2
- Sep 12, 2016.
This is a fast paced, vendor agnostic, technical overview of the Big Data landscape. No prior knowledge of databases or programming is assumed. Use code KDNUGGETS to save - register now!
- Urban Sound Classification with Neural Networks in Tensorflow
- Sep 12, 2016.
This post discuss techniques of feature extraction from sound in Python using open source library Librosa and implements a Neural Network in Tensorflow to categories urban sounds, including car horns, children playing, dogs bark, and more.
- The (Not So) New Data Scientist Venn Diagram
- Sep 12, 2016.
This post outlines a (relatively) new(er) Data Science-related Venn diagram, giving an update to Conway's classic, and providing further fuel for flame wars and heated disagreement.
- KDnuggets part-time, paid internship in Data Science, Data Journalism
- Sep 10, 2016.
KDnuggets is looking for graduate students in Business Analytics, Data Science or related topics for a part-time (5-10 hrs/week) paid internship, to help publish the site, do data journalism, and more.
- Automating Data Ingestion: 3 Important Parts
- Sep 9, 2016.
In the day and age of ‘Big Data”, data ingestion has to be automated on some level. How best to automate it?
- Data Science for IoT course: Strategic foundation for decision makers
- Sep 9, 2016.
The course is based on an open problem solving methodology for IoT analytics which we are developing within the course. The course starts in Sept 2016. To sign up or learn more email info@futuretext.com.
- Big Data is Too Big to Die
- Sep 9, 2016.
As the traditionalist data analytics professionals dig their heels in and refuse to give in to the Big Data deluge, it is fast becoming clear that the volume of evidence for the new movement is too substantial to deny.
- Doing the Data Science That Drives Predictive Personalization
- Sep 9, 2016.
Agile collaboration within data science teams is essential to the vision of customer analytics and personalization. Attend IBM DataFirst Launch Event on Sep 27 in New York City to engage with open-source community leaders and practitioners.
- Deep Learning Reading Group: Deep Networks with Stochastic Depth
- Sep 8, 2016.
An concise overview of a recent paper which introduces a new way to perturb networks during training in order to improve their performance, stochastic depth networks.
- A Beginner’s Guide To Understanding Convolutional Neural Networks Part 2
- Sep 8, 2016.
This is the second part of a thorough introductory treatment of convolutional neural networks. Have a look after reading the first part.
- 3 Reasons to Attend PAW New York
- Sep 8, 2016.
Register for Predictive Analytics World for Business - scheduled for Oct 23-27 in New York - the leading event for the business applications of data science. Register now and save an additional $150 with code KDN150.
- Top KDnuggets tweets, Aug 31 – Sep 06: Everyone else data is smaller than you think
- Sep 7, 2016.
Everyone else data is smaller than you think; Cartoon: Data Scientist - the sexiest job of the 21st century until ... ; Amazon gets new UK presence, hires top #MachineLearning researcher Neil Lawrence, his team.
- Big Data Dilemma: Save Me Money Versus Make Me Money
- Sep 7, 2016.
Does your organization see Big Data as an opportunity to “Save Me More Money”, or does your organization see Big Data as an opportunity to “Make Me More Money”?
- Up to Speed on Deep Learning: July Update, Part 2
- Sep 7, 2016.
Check out this second installation of deep learning stories that made news in July. See if there are any items of note you missed.
- Introducing Dask for Parallel Programming: An Interview with Project Lead Developer
- Sep 7, 2016.
Introducing Dask, a flexible parallel computing library for analytics. Learn more about this project built with interactive data science in mind in an interview with its lead developer.
- Webinar: Modern Regression Modeling for Voter MicroTargeting, Sep 14, Sep 21
- Sep 7, 2016.
Join us for a special 2-part webinar about voting trends, and we will show how machine learning models and data science can be used in elections.
- How to Become a Data Scientist – Part 3
- Sep 6, 2016.
This is the third and final part of a thorough, in-depth overview of becoming a data scientist, written by a recruiter in the field. This part focuses on the job market.
- A Beginner’s Guide To Understanding Convolutional Neural Networks Part 1
- Sep 6, 2016.
Interested in better understanding convolutional neural networks? Check out this first part of a very comprehensive overview of the topic.
- See You at the Top Data Conference: TDWI Austin
- Sep 6, 2016.
TDWI Austin is coming soon. Register at Super Early Bird prices by October 14, 2016, and save up to $890 with KDnuggets priority code KD890!
- The Acceleration of Data Science Excellence
- Sep 6, 2016.
If you’re a working data scientist, data engineering, or data application developer, attend IBM DataFirst Launch Event on Sep 27 in New York City. Engage with open-source community leaders and practitioners and learn how to accelerate your processes for putting data to work.
- Top August Stories: The 10 Algorithms Machine Learning Engineers Need to Know; How to Become a Data Scientist
- Sep 6, 2016.
Also - A Beginner Guide to Neural Networks with R; Data Science for Beginners: Fantastic Introductory Video Series from Microsoft.
- Top Stories, Aug 29-Sep 4: How Convolutional Neural Networks Work; Activation Functions in Neural Networks
- Sep 5, 2016.
How Convolutional Neural Networks Work; Activation Functions in Neural Networks; The 10 Algorithms Machine Learning Engineers Need to Know; How to Become a Data Scientist; Learning from Imbalanced Classes
- Top /r/MachineLearning Posts, August: Google Brain AMA, Image Completion with TensorFlow, Japanese Cucumber Farming
- Sep 5, 2016.
Google Brain AMA; Image Completion with Deep Learning in TensorFlow; Japanese Cucumber Farming; Andrew Ng's machine learning class in Python; Google Brain datasets for robotics research
- Cartoon: Labor Day in the era of Robotics
- Sep 5, 2016.
Amidst all the discussion about robots and automation taking over human jobs, new KDnuggets cartoon looks at how Labor Day can evolve by 2050.
- The Evolution of IoT Edge Analytics: Strategies of Leading Players
- Sep 2, 2016.
This article explores the significance and evolution of IoT edge analytics. Since the author believes that hardware capabilities will converge for large vendors, IoT analytics will be the key differentiator.
- Upcoming Meetings in Analytics, Big Data, Data Mining, Data Science: September and Beyond
- Sep 2, 2016.
Coming soon: Big Data Innovation Boston, Cypher 2016 Bangalore, ECML PKDD, MLconf Altanta, Strata + Hadoop World NYC, Strata AI, and many more.
- The Human Vector: Incorporate Speaker Embeddings to Make Your Bot More Powerful
- Sep 2, 2016.
One of the many ways in which bots can fail is by their (lack of) persona. Learn how speaker embeddings can help with this problem, and can help improve the persona of your bot.
- Insurance Analytics Europe, 5-6 October, London, UK
- Sep 2, 2016.
The Insurance Analytics Europe Summit will bring together 200+ insurance executives to explore both innovation in the insurance industry and uncover strategies to better use analytics capabilities. Use KD100 code to save on registration.
- 7 Big Data Steps in Health Science
- Sep 1, 2016.
Our doctors are now getting help from Big Data, which is becoming more entrenched and more crucial to reducing the investment needed to keep us healthy. But, how does Big Data actually do this?
- Data Science vs Crime: Detecting Pickpocket Suspects from Transit Records
- Sep 1, 2016.
A team of US and Chinese researchers has creatively used massive data collected by automated fare collectors for identifying thieves in the public transit systems. The system was tested in Beijing and was able to identify 93% of known pickpockets.
- HPE Haven OnDemand: Powerful Data Connectors for the Cloud and Enterprise
- Sep 1, 2016.
HPE Haven OnDemand simplifies how you can interact with data, allowing it to be transformed into an asset anytime, anywhere. Find out how the Connector APIs can facilitate this interaction.
- More answers, less theory from Big Guns at Big Data LDN, Nov 3-4
- Sep 1, 2016.
This new free-to-attend conference seeks to help businesses debunk Big Data myths with real-life case studies, and is expected to attract 3000 attendees over two days.
