Topics: 
) KDnuggets™ News 15:n23, Jul 22: Deep Learning Adversarial Examples Myths & Facts; Stop Hiring Data Scientists Until …
Deep Learning Adversarial Examples - facts and myths; Stop Hiring Data Scientists Until; arXiv.org and the 24 Hour Research Cycle; Statistics Denial Myth and Repackaging Statistics.
Features | Tutorials | Opinions | Interviews | News | Webcasts | Courses | Meetings | Jobs | Publications | Tweets | Quote
Features
Deep Learning Adversarial Examples - Clarifying Misconceptions
- Stop Hiring Data Scientists Until You're Ready for Data Science
- arXiv.org and the 24 Hour Research Cycle
- Statistics Denial Myth: Repackaging Statistics With Straddling Terms
- Jun 2015 Analytics, Big Data, Data Mining Acquisitions and Startups Activity
Tutorials, Overviews, How-Tos
Opinions
- Analyzing and Visualizing Flows in Rivers and Lakes with MATLAB
- OpenImpact - solve social problems with your data skills
- Big Data - yes, that's what a latest Sensational Rap Music Video is all about
Interviews
- Interview: Ali Vanderveld, Groupon on How Data Science is Changing the Global E-commerce Marketplace
- Interview: Ali Vanderveld, Groupon on Vital Ingredients of Analytics-powered Sales Force
- Interview: Ramkumar Ravichandran, Visa on Customer-focus Mindset for Analytics
News
- Top stories for Jul 12-18: 50+ Data Science, Machine Learning Cheat Sheets; Deep Learning Adversarial Examples - Misconceptions
- Top June stories: Top 20 Python Machine Learning Projects; Which Big Data, Data Mining Tools go together?
- CHEMDNER competition: Chemical and drug name recognition task in patents
- IEEE ICDM 2015 Call For Research and Service Award Nominations
Webcasts and Webinars
Courses
Meetings
- CYPHER 2015, Analytics India Summit - 12 Sep, Bangalore, India
- IAPA Challenge the Chief Analytics Event, Sydney, Aug 4
Jobs
- U. of California San Diego: Data Analytics Analyst (77011)
- Geisinger: Senior-level, High Performance Computing Programmer
- Digital Catapult Centre: Lead Technologist - Data (Permanent or Contract)
- Ford: Data Scientist - Connectivity Analytics Supervisor
- Manhattan Associates: Senior Operations Research Analyst - Data Scientist
- Mitra Capital: Data Scientist/Machine Learning Engineer
- SAS: Machine Learning Algorithm Research/Developer
- U. of Chicago Center for Data Science and Public Policy: Postdoc, Pre-Doctoral, Data Engineer, Data Scientist, and Project Manager
- Jigsaw Academy: Analytics and Big Data Experts
Publications
- New Book: Mining Latent Entity Structures
- Young Data Scientist Book: Inspiration for the future
- Book: Healthcare Data Analytics
- Predictive Policing - Free Book
Top Tweets
Quote
Myth: Deep learning is more vulnerable to adversarial examples than other kind of machine learning. Fact: So far we have been able to generate adversarial examples for every model we have tested. Ian Goodfellow (Google), Deep Learning Adversarial Examples - Clarifying Misconceptions
