InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
-
Introduction to Spring Data
Greg Turnquist explains how Spring Data avoids writing data queries by hand and provides the means to avoid SQL lock-in and connect to multiple data stores.
/presentations/intro-spring-data/en/mediumimage/Gregbig.JPG)
-
Intuition Engineering
Casey Rosenthal talks about a new discipline called Intuition Engineering and Vizceral, a tool they built at Neflix to process massive amounts of visual data in parallel.
/presentations/netflix-vizceral-intuition-engineering/en/mediumimage/Casbig.JPG)
-
TensorFlow: A Flexible, Scalable & Portable System
Rajat Monga talks about why Google built TensorFlow, an open source software library for numerical computation using data flow graphs, and what were some of the technical challenges in building it.
/presentations/tensorflow/en/mediumimage/Rajbig.JPG)
-
Targeting Your Audience: Data Visualization to Communicate Data Insights
Randy Krum explains how to use the power of data visualization to convey actionable insights to an audience, making data clear and memorable by showing the audience what the data means.
/presentations/data-visualization-data-insight/en/mediumimage/Ranbig.JPG)
-
Visual Rules of the Road for Big Data Practitioners
David Fisher discusses via example how to build a data navigation language into visualizations, providing an intuitive user experience via the mechanism of subtle visual cuing.
/presentations/visual-rules-data/en/mediumimage/Davidbig.JPG)
-
Forecasting Using Data - Quickly Answering How Big, How Long and How Likely
Troy Magennis explains in this workshop how to capture data and use it for reliable project forecasting using a practical and simple approach to forecasting without item effort estimation.
/presentations/forecasting-data/en/mediumimage/Trobig.JPG)
-
Impact of Machine Learning Systems in Industries
The panelists discuss the impact machine learning is having on various industries.
/presentations/machine-learning-industries/en/mediumimage/panelbig.jpg)
-
But I Need a Database that _Scales_
Aaron Spiegel reviews common scaling techniques for both relational and NoSQL databases, discussing trade-offs of these techniques and their effect on query flexibility, transactions and consistency.
/presentations/database-scalability-techniques/en/mediumimage/Aaronbig.JPG)
-
Cassandra and DataStax Enterprise on PCF
Ben Lackey and Cornelia Davis start with the use cases for on-demand, dedicated DSE clusters, cover the solution design, and demo the system, touching also the support that Spring has for Cassandra.
/presentations/cloud-foundry-cassandra-datastax/en/mediumimage/12big.jpg)
-
ETL Is Dead, Long Live Streams
Neha Narkhede shares the experience at LinkedIn moving from ETL to real-time streams, the challenges of scaling Kafka to hundreds of billions of events/day, supporting thousands of engineers, etc.
/presentations/etl-streams/en/mediumimage/neabig.JPG)
-
MLeap: Release Spark ML Models
Hollin Wilkins discusses the reasons behind MLeap, outes the programming time saved by using it, shows benchmarks of several online models, and provides a demo and examples of using it in practice.
/presentations/mleap/en/mediumimage/doibig.JPG)
-
Elasticsearch for SQL Users
Shaunak Kashyap looks at several well-understood concepts and SQL queries from the relational paradigm and maps these to their Elasticsearch equivalents.
/presentations/elasticsearch-sql/en/mediumimage/Shabig.JPG)