InfoQ Homepage Data Model Content on InfoQ
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Posted by
Nicholas Mitchell
on
May 31, 2021
Scaling & Optimizing the Training of Predictive Models
Nicholas Mitchell presents the core building blocks of an entire toolchain able to deal with challenges of large amounts of data in an industrial scalable system.
on May 31, 2021Icon21:39 -
Posted by
Vincent Warmerdam
on
Jul 02, 2020
Accuracy as a Failure
V. Warmerdam talks about cautionary tales of mistakes that might happen when we let data scientists on a goose chase for accuracy. Highly accurate models are more damaging than the inaccurate ones
on Jul 02, 2020Icon54:11 -
Posted by
Matthew Tovbin
on
Oct 28, 2018
Implementing AutoML Techniques at Salesforce Scale
Matthew Tovbin shows how to build ML models using AutoML (Salesforce), including techniques for automatic data processing, feature generation, model selection, hyperparameter tuning and evaluation.
on Oct 28, 2018Icon39:16 -
Posted by
Sahil Dua
on
Jun 01, 2018
Tools to Put Deep Learning Models in Production
Sahil Dua discusses how Booking.com supports data scientists by making it easy to put their models in production, and how they optimize their model prediction infrastructure for latency or throughput.
on Jun 01, 2018Icon36:10 -
Posted by
Scott Clark
on
Feb 07, 2017
Using Bayesian Optimization to Tune Machine Learning Models
Scott Clark introduces Bayesian Global Optimization as an efficient way to optimize ML model parameters, explaining the underlying techniques and comparing it to other standard methods.
on Feb 07, 2017Icon38:49 -
Posted by
Juan Batiz-Benet
on
Mar 13, 2016
Data Structures in and on IPFS
Juan Batiz-Benet makes a short intro of IPFS (the InterPlanetary File System) and discusses the IPLD data model and example data structures (unixfs, keychain, post).
on Mar 13, 2016Icon48:32 -
Posted by
Mark Derricutt
on
Mar 02, 2016
Towards Immutable Resources
Mark Derricutt discusses the importance of having different read and write data models when working with RESTful web APIs.
on Mar 02, 2016Icon30:46 -
Posted by
Adam Ernst
on
Nov 08, 2014
The Functional Programming Concepts in Facebook's Mobile Apps
Adam Ernst shows how his team at Facebook encountered spiraling complexities and declining reliability and decided to make the shift to functional, in the data model and the view layer of News Feed.
on Nov 08, 2014Icon35:55 -
Posted by
Sean Cribbs
on
Aug 10, 2014
Data Modeling for Scale with Riak Data Types
Sponsored by Basho. Sean Cribbs discusses the theory behind several rich data types introduced with Riak 2.0 and then walking through some example applications that use them in popular languages.
on Aug 10, 2014Icon44:17 -
Posted by
Garrett Eardley
on
Dec 12, 2013
Tracking Millions of Ganks in Near Real Time
Garrett Eardley explores how Riot Games is using Riak for their stats system, discussing why they chose Riak, the data model and indexes, and strategies for working with eventually consistent data.
on Dec 12, 2013Icon38:01 -
Posted by
Robin Johnson
on
Sep 08, 2013
How Draw Something Scaled To 50 million New Users, in 50 Days, with Zero Downtime
Robin Johnson discusses using a data management model for games that can be scaled, and the bottlenecks and challenges met by OMGPOP scaling to millions of users.
on Sep 08, 2013Icon43:56 -
Posted by
Claudia Perlich
on
Jun 16, 2013
The Big Data Revolution
Claudia Perlich keynotes on M6D’s approach to Big Data, using data granularity to build predictive models used for user targeting, bid optimization and fraud detection.
on Jun 16, 2013Icon59:33