- 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.
- 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.
- 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.
- Emory University: Tenure-Track Faculty Position in Data Exploration - Sep 26, 2016.
We are particularly interested in applicants with expertise in interactive data exploration, broadly construed, which includes data mining, analytics, visualization, human-computer interaction, and summarization.
- 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.
- U. of Iowa, Tippie College of Business: Faculty Position: Chair in Business Analytics - Sep 22, 2016.
Tenure-track Full Professor position in business analytics beginning August 2017. Areas of interest include but are not limited to data-driven research in machine learning, data science, statistics, optimization, and transportation.
- Baidu: Research Scientist - Sep 22, 2016.
Baidu is looking for research scientists and engineers with strong background in machine learning, natural language processing, data mining, computer vision and system engineering.
- 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.
- Apple: Data Science Engineer - Sep 22, 2016.
Seeking a Data Science Engineer to lead the design and implementation of systems and tools to support the fraud prevention efforts of Analytic Insight.
- Rowan University: CS Faculty – Data Analytics (open rank) - Sep 22, 2016.
The Computer Science Department at Rowan University invites applications for a tenure-track faculty position with a primary specialization in Data Analytics to begin September 1, 2017. Applications due Nov 15, 2016.
- 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.
- CSU East Bay: Asst/Assoc. Professor of Management (Information Technology) - Sep 21, 2016.
We are particularly interested in candidates with experience and expertise in big data technologies and applications. Appointment will begin in fall quarter, 2017.
- 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.
- WPI: Professor (Open Rank) – Data Science - Sep 21, 2016.
The Data Science program invites applications for a tenure track (open rank) Professor position with a research focus in Data Science to begin in the Fall of 2017 to strengthen this important interdisciplinary area.
- 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™ News 16:n34, Sep 21: The Great Algorithm Tutorial Roundup; 7 Steps to Mastering Apache Spark 2.0 - Sep 21, 2016.
The Great Algorithm Tutorial Roundup; 7 Steps to Mastering Apache Spark 2.0; Machine Learning in a Year: From Total Noob to Effective Practitioner; Learning From Data (Introductory Machine Learning) Caltech MOOC
- 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.
- Mid-Atlantic PERMANENTE Medical Group: Research Data Analyst - Sep 20, 2016.
Provide analytic support on research projects involving clinical data, including collaborating with investigators in research studies, designing databases for research projects, and running analytical reports and statistics. Previous healthcare experience required.
- 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!
- CSC Venture Capital: Quantitative Analyst - Sep 20, 2016.
Seeking a Quantitative Analyst to join the investment team, to help identify insights in large unstructured data sets and develop, analyze and deploy quant-based investment decision support tools for early stage private technology investment.
- 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.
- Change Dynamix: Lead Data Scientist - Sep 19, 2016.
Seeking an experienced Data Scientist who can transform our data into valuable insights, working to understand the objectives of our customers, model data, choose analytical techniques, and develop novel approaches to machine learning within our market.
- 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.
- Fusion Media Group – Univision Communications: Data Scientist - Sep 16, 2016.
Help develop groundbreaking data-driven solutions and products to advance our growing digital and linear businesses.
- 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.
- University of Wisconsin – Stevens Point: Sentry Insurance Endowed Chair in Business Analytics - Sep 15, 2016.
We are particularly interested in candidates with interest in developing relationships with local businesses and partners, and industry or academic experience in business or data analytics.
- 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.
- Capital Match (Singapore): Head of Data Science - Sep 14, 2016.
Experienced data scientist / SW engineer with passion for data for a role of the Head of Data Science. Data science needs impact every stage of our work flow - customer acquisition, operational automation, risk and underwriting, portfolio servicing, and product development.
- KDnuggets™ News 16:n33, Sep 14: Top Algorithms Used by Data Scientists; (Not So) New Data Scientist Venn Diagram - Sep 14, 2016.
Top Algorithms Used by Data Scientists; Guide To Understanding Convolutional Neural Nets; The (Not So) New Data Scientist Venn Diagram; Deep Learning Networks with Stochastic Depth.
- 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.
- University of Wisconsin – Stevens Point: Assistant/Associate Professor - Sep 13, 2016.
Apply for Sentry Insurance Endowed Chair in Computational Analytics, starting August 2017. The candidate is expected to teach undergraduate courses in Data Analytics, and possibly graduate courses in an online MS in Data Science.
- 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.
- 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 firstname.lastname@example.org.