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.
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.
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.
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.
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 #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.
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."
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.
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.
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.
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.
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!
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
For data science beginners, 3 elementary issues are given overview treatment: supervised vs. unsupervised learning, decision tree pruning, and training vs. testing datasets.
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.
Support Vector Machines remain a popular and time-tested classification algorithm. This post provides a high-level concise technical overview of their functionality.
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.
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.
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.
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.
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!
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.
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.
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 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
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.
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.
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.
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.
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.
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.
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.
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...
The Slang Sentiment Dictionary (SlangSD) includes over 90,000 slang words together with their sentiment scores, facilitating sentiment analysis in user-generated contents.
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.
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.
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.
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.
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.
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.
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.
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 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!
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
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.
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!
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.
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 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.
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.
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.
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.
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.
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.
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.
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”?
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.
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.
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.
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
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
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.
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.
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.
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?
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 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.
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.
Top Data Scientist Claudia Perlich on Biggest Issues in Data Science
Data Science for Internet of Things (IoT): Ten Differences From Traditional Data Science
Top Algorithms and Methods Used by Data Scientists
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