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**Announcements**

**Webinar: Flipping the 80/20 Rule for Analytics -**Hear how Teradata helps businesses flip the 80/20 model so they can spend only 20% preparing and organizing data and 80% on the analytics, accelerating time to value. Learn to reduce the friction of data preparation and apply machine-learning techniques such as sentiment, text, path, and graph analytics. Register to attend.

**Featured**

- How Apple Uses Big Data To Drive Success * - By Bernard Marr
- Data Integrity: The Rest of the Story (Part II) *
- Are you smart enough to work at Google? *
- 10 Python Machine Learning Projects on GitHub *
- 9 Python Analytics Libraries *
- Big Data: Uncovering The Secrets of Our Universe At CERN * - By Bernard Marr
- Four successful big data / analytics startups in Seattle *
- Measuring Information Retrieval Performance Using Extrapolated Prec...*
- Failing with a purpose (Morning Analytics Coffee Blog) *
- 100 Best Data Science Companies to Work for in 2015
- How Do I Become a Data Scientist?
- The Handbook Of Data science
- Self-learning Machines & Deep Convolutional Neural Networks Cla...
- Morning Analytic Coffee Blog
- Statistics about the #Spark community
- Hadoop – Whose to Choose
- An Introduction to Deep Learning and it’s role for IoT/ future cities
- Data science to understand and fight cancer +
- Web Crawling & Analytics Case Study - Database Vs Self Hosted M...
- Machine Learning Resources for Spam Detection
- Data Science and its problems
- UV and Sun exposure good to protect you against skin cancer, says d...
- The Institutional Response

**News, Events, Books, Training, Forum Questions**

- Python (and R) for Data Science - sample code, libraries, projects,...*
- New textbook on data mining *
- Flipping the 80/20 Rule for Analytics * - Teradata Webinar
- Data Science Central’s Upcoming Educational Webinar Series *
- Question: Forecasting Digital Wallet Market in the US *
- Speed up big data queries by up to 1000x with Pivotal HAWQ *
- 5-Day Hands-On Data Science & Engineering Bootcamp *
- Predictive Analytics Demystified - IBM Video
- Question: About pattern recognition to solve deadly Amtrak crash
- Question: How to determine the optimum number of variables?
- The power of IBM SPSS Statistics and R together - White Paper
- Whitepaper: The Power of R and Visual Analytics
- Building a Predictive Analytics Solution with Azure ML
- What Defines a Big Data Scenario? - Infographics
- Event: Intro to Apache Ignite & Semi-supervised Learning
- Big Data Innovation Summit
- Discover data-led innovation at Big Data Analytics 2015
- Predictive Analytics World Boston 2015
- Big Data Bootcamp - August 28 to 30, Austin
- Big Data Developer Conference - August 17 to 19, Seattle
- Rosslyn Analytics Pioneers Analytics-as-a-Service on Microsoft Azure

**Picture of the Week**

*Source for picture: see featured article marked with +*

**On DSC Channels**

- An indispensable Python : Data sourcing to Data science
- The Data Science Ecosystem in One Tidy Infographic
- Digesting Big Data
- Understanding the nature of IoT data
- Big Data: From a junk yard to a gold mine
- Building blocks of data science
- Hadoop is Dead. DataFlow is Alive!
- Contradictions of Big Data

**Quote of the Week**:

*Unlike statistics, data science tends to use algorithms rather than models, to make predictions, even to compute confidence intervals.*

**Links**

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