---

Features | Software | Opinions | Interviews | Reports | News | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets | CFP | Quote



Features

• The Myth of Model Interpretability - Apr 27, 2015.
  
  Deep networks are widely regarded as black boxes. But are they truly uninterpretable in any way that logistic regression is not?
• Data Mining: New Comprehensive Textbook by Charu Aggarwal - Apr 23, 2015.
  
  This comprehensive data mining textbook explores the different aspects of data mining, from basics to advanced, and their applications, and may be used for both introductory and advanced data mining courses.
• New Hybrid Rare-Event Sampling Technique for Fraud Detection - Apr 26, 2015.
  
  Proposed hybrid sampling methodology may prove useful when building and validating machine learning models for applications where target event is rare, such as fraud detection.
• Deep Learning to Fight Crime - Apr 22, 2015.
  
  We look at how using Deep Learning, Spark, and H2O Machine Learning platform can be used to analyze and predict crime in San Francisco and Chicago.
• Interview: Emmanuel Letouze, Data-Pop Alliance on Big Data for Development and Future Prospects - Apr 25, 2015.
  
  We discuss the field of Big Data for Development, current projects and future plans for Data-Pop Alliance, public participation opportunities, advice, and more.
• Big Data Bootcamp, Austin: Day 3 Highlights - Apr 24, 2015.
  
  Highlights from the presentations by Big Data and Analytics leaders/consultants: time-series analytics, Hadoop Solutions Value Matrix, and more.

 
 Software  (see also All Software )

• HappyGrumpy - Free Twitter Sentiment Analysis and Data - Apr 24, 2015.
  
  HappyGrumpy has made available interesting data of Twitter sentiment changes and sentiment distribution around the world, by country, and over time.

 
 Opinions  (see also All Opinions for this month )

• How to become a Data Scientist - brief answer - Apr 28, 2015.
  
  The most important steps to become a Data Scientist: learn Python, deep understanding of machine learning, try to be up-to-date. Check more details in the post.
• MapR on Open Data Platform: Why we declined - Apr 24, 2015.
  
  Why MapR declined to participate in the Open Data Platform? Our concerns include redundancy with Apache Software Foundation Governance, misdefined "core", and lack of participation from Hadoop leaders.

 
 Interviews  (see also All Interviews for this month )

• Interview: Mario Vinasco, Facebook on Advancing Marketing Analytics through Rigorous Experimentation - Apr 27, 2015.
  
  We discuss marketing analytics at Facebook, multi-channel performance assessment, success factors, lessons from Look Back feature, advice, and more.
• Interview: Emmanuel Letouze, Data-Pop Alliance on Democratizing the Benefits of Big Data - Apr 24, 2015.
  
  We discuss the 3 Cs of Big Data, state of ethics in the field of Big Data, and how to ensure that the benefits of Big Data reach the masses.
• Interview: Emmanuel Letouze, Data-Pop Alliance on the Role of Big Data in Economic Development - Apr 23, 2015.
  
  We discuss the emerging Big Data ecosystem, its key players, and the severe consequences of inadequate statistical capabilities across many African nations.
• Interview: Emmanuel Letouze, Data-Pop Alliance on Big Data and Human Rights - A Complex Affair - Apr 22, 2015.
  
  We discuss the founding story of Data-Pop Alliance, the applications and implications of Big Data on Human Rights and the need for penetration of Data Literacy.

 
 Reports  (see also All Reports for this month )

• Big Data Bootcamp, Austin: Day 2 Highlights - Apr 23, 2015.
  
  Highlights from the presentations by Big Data and Analytics leaders/consultants on day 2 of Big Data Bootcamp in Austin.
• Big Data Bootcamp, Austin: Day 1 Highlights - Apr 22, 2015.
  
  Highlights from the presentations by Big Data and Analytics leaders/consultants on day 1 of Big Data Bootcamp 2015 in Austin.

 
 News  (see also All News )

• Kaggle Competition (Facebook recruiting): Human or Robot? - Apr 28, 2015.
  
  Facebook and Kaggle are launching an Engineering competition for 2015 - leaders will earn an opportunity to interview for a software engineer at Facebook, working on world class Machine Learning problems. In this competition, you'll be chasing down robots for an online auction site.
• Top /r/MachineLearning Posts, Apr 19-25: Neural nets for nipple detection; NHL Goal celebration hack - Apr 27, 2015.
  
  Convolutional neural nets and Android App for nipple detection (NSFW), NHL goal detection, Geoff Hinton recent AI talk, top machine learning podcasts, and matrix multiplication in deep learning.
• Top stories for Apr 19-25: Top LinkedIn Groups for Analytics, Big Data, Data Mining; 10 R Packages for a Kaggle Champion - Apr 26, 2015.
  
  Top LinkedIn Groups for Analytics, Big Data, Data Mining, and Data Science - from "Big Bang to Now"; Top 10 R Packages to be a Kaggle Champion; Deep Learning to Fight Crime.
• Top /r/MachineLearning Posts, Apr 12-18: Andrew Ng AMA, Autoencoders, and Deep Learning Textbooks - Apr 23, 2015.
  
  Andrew Ng's AMA, a probabilistic view of Autoencoders, open source sentiment analysis, deep learning textbooks, and Airbnb's host matching are all discussed this week on /r/MachineLearning.

 
 Webcasts and Webinars  (see also All Webcasts and Webinars )

• Webinar: Data Mining: Failure to Launch
  [May 5] - Apr 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 May 5.
• Upcoming Webcasts on Analytics, Big Data, Data Science - Apr 28 and beyond - Apr 27, 2015.
  
  Solving Big Data Challenges, Implementing a Better Search Experience, Data Scientists Compensation, Maximizing ROI, Identifying Customers Across Platforms, The Fast Data Challenge with Michael Stonebraker, and more.

 
 Courses  (see also All Courses )

• Text Analytics, Text Mining Courses on Statistics.com - Apr 28, 2015.
  
  Text analytics or text mining is the natural extension and essential part of predictive analytics and Data Science - learn key skills with Statistics.com online courses.
• TMA Predictive Analytics Data Mining Training [Wash. DC, May | Toronto, Aug] - Apr 28, 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 Washington DC (May), Toronto (Aug).
• Data Science Open House Apr 29, Online or In-Person, NYC - Apr 24, 2015.
  
  Data science educator Metis, creators of the Metis Data Science Bootcamp in New York City, are hosting Apr 29 open house, in person in NYC and live online. Attend to meet the instructors, students and alumni.
• Salford Quickstart Data Mining Training in Washington, DC, May 15 - Apr 23, 2015.
  
  Get step-by-step instruction for the most popular data mining techniques, be able to start your own data mining projects, apply your new data mining knowledge to create immediate value.
• Data Lakes for Big Data, Free MOOC from EMC - Apr 23, 2015.
  
  What can Big Data and Data Lakes do for you? Find out in our FREE Data Lakes for Big Data MOOC.

 
 Meetings  (see also All Meetings )

• Open drives Boston Open Data Science Conference, May 30-31 - Apr 25, 2015.
  
  Data science is built on transparency, effort, and the exchange of ideas. Join Open Data Science Conference, Boston, May 30-31, 2015.

 
 Jobs  (see also All Jobs )

• Boeing: Advanced Info Technologist in Machine Learning - Apr 28, 2015.
  
  This position is focusing on Machine Learning and Data Mining with a strong background in statistics, probability, mathematics, databases, and strong programming skills. Help build something better for yourself, for our customers and for the world.
• Boeing: Advanced Information Technologist Text Analytics - Apr 28, 2015.
  
  Join growing Boeing central R&D, Analytics and Simulation organization, and apply advanced data analysis and text analysis algorithms to help build something better for yourself, for our customers and for the world.
• Growth Intelligence: Developer, Big Data - Apr 28, 2015.
  
  Help collect and process data on millions of companies from many sources, scale back-end data platform, build and improve web application, analyse data, and extract useful insights. Our clients include Google, American Express and Vodafone.
• Growth Intelligence (London): Senior Data Scientist - Apr 28, 2015.
  
  Help us take the messy data we have on millions of companies and push it through a data pipeline into a web based search and recommendation engine. Our clients include Google, American Express and Vodafone.
• XO: Marketing Analyst IV (Data Scientist) - Apr 24, 2015.
  
  Develop game changing analytical, predictive and statistical solutions, develop and deploy models and algorithms to enhance business processes for marketing strategy and operations.
• Apple: Data Science Engineer - Apr 24, 2015.
  
  Customer-oriented, passionate and driven Data Science Engineer to lead our test automation and release management; be able to design and drive large projects from inception to production implementation and beyond.
• Boeing: Game Software Engineer - Apr 23, 2015.
  
  Help develop C++, OpenGL, and OpenGL Shader code to provide high-end visualization to new and existing simulation applications to support both commercial and defense programs.
• Boeing: Software Engineer Java Big Data Analysis - Apr 23, 2015.
  
  Develop code that helps to process, visualize, and analyze Big Data, including processing raw files, data standardization, integration, writing clean data to a database.
• Boeing: Advanced Information Technologist Data Architect - Apr 23, 2015.
  
  Help design and develop Big Data Databases, create Data Models, define and develop ETL procedures, and manage the overall ETL architecture to support commercial and defense programs.
• SEIU 775: Data Scientist (Research and Analytics) - Apr 22, 2015.
  
  Develop and build an ambitious portfolio of predictive modeling projects including learning outcomes, matching algorithms to connect home care aides with their consumers, and personalizing care plans for individual long-term care consumers.

 
 Academic and Research positions  (see also All Academic positions )

• U. of Bristol: Heilbronn Research Fellowship: Data analysis for cybersecurity - Apr 27, 2015.
  
  Three year Research Fellowships in the area of Internet data analysis for cybersecurity applications, starting (preferably) Oct 2015 or Jan 2016. Apply by May 31.

 
 Publications

• On the Shelf: Data Science Books - Apr 28, 2015.
  
  Here are some great books About Data Science, Data Science for Businesses, Data Science in Popular Culture, Data Science How Tos & Manuals, and more - brought to you by UC Berkeley online Master of Information and Data Science.

 
 Top Tweets  (see also All top tweets for this month )

• Top KDnuggets tweets, Apr 21-27 - Apr 28, 2015.
  
  Great discussion: Building #BigData systems in academia, industry;
  DeepLearning in a Nutshell - what it is, how it works, why care?;
  Basics of #DeepLearning to Get You Started;
  Top LinkedIn Groups for #Analytics, #BigData.

 
 CFP - Calls for Papers  (see also All Calls for Papers )

• Due May 10, RapidMiner Wisdom, Europe , Ljubljana, Slovenia. Aug 31-Sep 2, 2015
• Due Jun 5, 4th KDD Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM) , at KDD'15, Sydney, Australia. Aug 10, 2015
• Due Jun 19, Big Data and Analytics EdCon 2015 , Puerto Rico, USA. Aug 11-14, 2015.
• Due Jun 22, ECML/PKDD 2015 Workshop on Meta-learning & Algorithm Selection (MetaSel) , co-located with ECML/PKDD 2015, Porto, Portugal. Sep 7, 2015
• Due Jul 20, The 3rd Int. Workshop on High Dimensional Data Mining (HDM 2015) , at IEEE International Conference on Data Mining (IEEE ICDM 2015), Atlantic City, NJ, USA. Nov 13, 2015.

 
 

Quote

Get your hands dirty. Implement most important methods by yourself to get more understanding, experience and fun. It was a really great memory when I saw first time that my neural net can recognize digits, Mateusz Opala How to become a Data Scientist - brief answer