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38:06
Data Science Follow 209 Followers

Structuring Data for Self-Serve Customer Insights

Posted by Jim Porzak  on  Aug 12, 2016 Posted by Jim Porzak Follow 0 Followers  on  Aug 12, 2016

Jim Porzak discusses creating an analyst ready data mart that is complete at different levels of abstraction and models customer decision points in order to be able to understand customers.

30:44
Data Science Follow 209 Followers

Monitoring and Troubleshooting Real-Time Data Pipelines

Posted by Alan Ngai  on  Jul 20, 2016 Posted by Alan Ngai Follow 0 Followers , Premal Shah Follow 0 Followers  on  Jul 20, 2016

Alan Ngai and Premal Shah discuss best practices on monitoring ​distributed real-time data processing frameworks and how DevOps can gain control and visibility over these data pipelines.

01:00:34
Data Science Follow 209 Followers

Solving Business Problems with Data Science

Posted by Krishna Sankar  on  Jul 08, 2016 Posted by Krishna Sankar Follow 0 Followers , Robert Bernard Follow 0 Followers , Mohamed Elmallah Follow 0 Followers , Shankar Vedaraman Follow 0 Followers  on  Jul 08, 2016

The panelists discuss some of the unique problems that only data science can solve, the pitfalls and the success rate of data science projects.

27:05
Data Science Follow 209 Followers

Hybrid Artificial Intelligence

Posted by Manuel Ebert  on  Jul 08, 2016 Posted by Manuel Ebert Follow 0 Followers  on  Jul 08, 2016

Manuel Ebert explores how hybrid AI works, its impact on businesses, using it in existing businesses, and what we can expect from hybrid artificial intelligence in the years to come.

40:09
Data Science Follow 209 Followers

Building a Predictive Intelligence Engine

Posted by Viral Bajaria  on  Jun 24, 2016 Posted by Viral Bajaria Follow 0 Followers  on  Jun 24, 2016

Viral Bajaria explains a formula for reaching the B2B buyer early in the sales cycle by tying together billions of rows of customer data and overlaying predictive intelligence technology.

50:05
Data Science Follow 209 Followers

The Future of Data Science

Posted by Milind Bhandarkar  on  Jun 19, 2016 Posted by Milind Bhandarkar Follow 0 Followers , Peter Bakas Follow 0 Followers , Leo Li Follow 0 Followers , Pushpraj Shukla Follow 0 Followers , Mike Tamir Follow 0 Followers , Alexander Lavin Follow 0 Followers  on  Jun 19, 2016

The panelists discuss some of the trends in data science today, the job of a data scientist, the tools and other related issues.

32:32
Data Science Follow 209 Followers

Detecting Anomalies in Streaming Data, Evaluating Algorithms for Real-World Use

Posted by Alexander Lavin  on  Jun 01, 2016 Posted by Alexander Lavin Follow 0 Followers  on  Jun 01, 2016

Alexander Lavin introduces the Numenta Anomaly Benchmark (NAB), a framework for evaluating anomaly detection algorithms on streaming data.

37:06
Data Science Follow 209 Followers

Predicting the Future: Surprising Revelations trom Truly Big Data

Posted by Pushpraj Shukla  on  May 24, 2016 Posted by Pushpraj Shukla Follow 0 Followers  on  May 24, 2016

Pushpraj Shukla discusses how Microsoft Bing predicts the future based on aggregate human behavior using one of the largest scale data sets, and recent progress in large scale deep learnt models.

40:32
Data Science Follow 209 Followers

Netflix Keystone - How We Built a 700B/day Stream Processing Cloud Platform in a Year

Posted by Peter Bakas  on  May 19, 2016 Posted by Peter Bakas Follow 0 Followers  on  May 19, 2016

Peter Bakas presents in detail how Netflix has used Kafka, Samza, Docker, and Linux to implement a multi-tenant pipeline processing 700B events/day in the Amazon AWS cloud.

41:26
Data Science Follow 209 Followers

Hunting Criminals with Hybrid Analytics

Posted by David Talby  on  May 10, 2016 Posted by David Talby Follow 0 Followers  on  May 10, 2016

David Talby demos using Python libraries to build a ML model for fraud detection, scaling it up to billions of events using Spark, and what it took to make the system perform and ready for production.

35:44
Data Science Follow 209 Followers

Big-Data Analytics Misconceptions

Posted by Irad Ben-Gal  on  May 03, 2016 Posted by Irad Ben-Gal Follow 0 Followers  on  May 03, 2016

Irad Ben-Gal discusses Big Data analytics misconceptions, presenting a technology predicting consumer behavior patterns that can be translated into wins, revenue gains, and localized assortments.

39:15
Data Science Follow 209 Followers

How Comcast Uses Data Science and ML to Improve the Customer Experience

Posted by Jan Neumann  on  May 01, 2016 1 Posted by Jan Neumann Follow 0 Followers  on  May 01, 2016 1

Jan Neumann presents how Comcast uses machine learning and big data processing to facilitate search for users, for capacity planning, and predictive caching.

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