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38:37
AI, ML & Data Engineering Follow 815 Followers

Interpretable Machine Learning Products

Posted by Mike Lee Williams  on  Jun 06, 2018 Posted by Mike Lee Williams Follow 0 Followers  on  Jun 06, 2018

Mike Lee Williams discusses how interpretability can make deep neural networks models easier to understand, and describes LIME, an OS tool that can be used to explore what ML classifiers are doing.

49:01
AI, ML & Data Engineering Follow 815 Followers

End-to-End ML without a Data Scientist

Posted by Holden Karau  on  May 30, 2018 Posted by Holden Karau Follow 3 Followers  on  May 30, 2018

Holden Karau discusses how to train models, and how to serve them, including basic validation techniques, A/B tests, and the importance of keeping models up-to-date.

42:26
AI, ML & Data Engineering Follow 815 Followers

Deep Learning for Science

Posted by Prabhat  on  May 30, 2018 Posted by Prabhat Follow 0 Followers  on  May 30, 2018

Prabhat discusses machine learning's impact on climatology, astronomy, cosmology, neuroscience, genomics, and high-energy physics, and the future of AI in powering scientific discoveries.

38:53
AI, ML & Data Engineering Follow 815 Followers

Liquidity Modeling in Real Estate Using Survival Analysis

Posted by Xinlu Huang  on  May 29, 2018 Posted by Xinlu Huang Follow 0 Followers , David Lundgren Follow 0 Followers  on  May 29, 2018

Xinlu Huang and David Lundgren discuss hazard and survival modeling, metrics, and data censoring, describing how Opendoor uses these models to estimate holding times for homes and mitigate risk.

49:58
AI, ML & Data Engineering Follow 815 Followers

Data Pipelines for Real-Time Fraud Prevention at Scale

Posted by Mikhail Kourjanski  on  May 23, 2018 Posted by Mikhail Kourjanski Follow 1 Followers  on  May 23, 2018

Mikhail Kourjanski discusses the architecture of PayPal’s data service which combines a Big Data approach with providing data in real time for decision making in fraud detection.

37:05
AI, ML & Data Engineering Follow 815 Followers

pDB: Scalable Prediction Infrastructure with Precision and Provenance

Posted by Balaji Rengarajan  on  May 23, 2018 Posted by Balaji Rengarajan Follow 0 Followers  on  May 23, 2018

Balaji Rengarajan describes the platform built on the Celect’s pDB framework, providing multiple use cases such as online personalization, document classification, and geospatial anomaly detection.

35:56
AI, ML & Data Engineering Follow 815 Followers

Self-Racing Using Deep Neural Networks: Lap 2

Posted by Jendrik Joerdening  on  May 23, 2018 1 Posted by Jendrik Joerdening Follow 1 Followers , Anthony Navarro Follow 1 Followers  on  May 23, 2018 1

Jendrik Joerdening and Anthony Navarro discuss how a team of Udacity students used neural networks to teach a car to drive by itself around a track in two days.

50:45
AI, ML & Data Engineering Follow 815 Followers

The Black Swan of Perfectly Interpretable Models

Posted by Mayukh Bhaowal  on  May 22, 2018 Posted by Mayukh Bhaowal Follow 0 Followers , Leah McGuire Follow 0 Followers  on  May 22, 2018

Mayukh Bhaowal, Leah McGuire discuss how Salesforce Einstein made ML more transparent and less of a black box, and how they managed to drive wider adoption of ML.

32:58
AI, ML & Data Engineering Follow 815 Followers

Counting is Hard: Probabilistic Algorithms for View Counting at Reddit

Posted by Krishnan Chandra  on  May 15, 2018 Posted by Krishnan Chandra Follow 0 Followers  on  May 15, 2018

Krishnan Chandra explains the challenges of building a view counting system at scale, and how Reddit used probabilistic counting algorithms to make scaling easier.

46:19
AI, ML & Data Engineering Follow 815 Followers

Developing Data and ML Pipelines at Stitch Fix

Posted by Jeff Magnusson  on  May 15, 2018 Posted by Jeff Magnusson Follow 0 Followers  on  May 15, 2018

Jeff Magnusson discusses thoughts and guidelines on how Stitch Fix develops, schedules, and maintains their data and ML pipelines.

33:49
AI, ML & Data Engineering Follow 815 Followers

Counterfactual Evaluation of Machine Learning Models

Posted by Michael Manapat  on  May 10, 2018 Posted by Michael Manapat Follow 0 Followers  on  May 10, 2018

Michael Manapat discusses how Stripe evaluates and trains their machine learning models to fight fraud.

49:20
AI, ML & Data Engineering Follow 815 Followers

Machine Learning Pipeline for Real-Time Forecasting @Uber Marketplace

Posted by Chong Sun  on  May 10, 2018 Posted by Chong Sun Follow 0 Followers , Danny Yuan Follow 3 Followers  on  May 10, 2018

Chong Sun and Danny Yuan discuss how Uber is using ML to improve their forecasting models, the architecture of their ML platform, and lessons learned running it in production.

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