InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Gimel: PayPal’s Analytics Data Platform
Deepak Chandramouli introduces and demos Gimel, a unified analytics data platform which provides access to any storage through a single unified data API and SQL.
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Understanding Software System Behavior with ML and Time Series Data
David Andrzejewski discusses how time series datasets can be combined with ML techniques in order to aid in the understanding of system behaviors in order to improve performance and uptime.
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Analyzing & Preventing Unconscious Bias in Machine Learning
Rachel Thomas keynotes on three case studies, attempting to diagnose bias, identify some sources, and discusses what it takes to avoid it.
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Orchestrating Data Microservices with Spring Cloud Data Flow
Mark Pollack discusses how to create data integration and real-time data processing pipelines using Spring Cloud Data Flow and deploy them to multiple platforms – Cloud Foundry, Kubernetes, and YARN.
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Models in Minutes not Months: AI as Microservices
Sarah Aerni talks about how Salesforce built an AI platform that scales to thousands of customers.
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Understanding ML/DL Models using Interactive Visualization Techniques
Chakri Cherukuri discusses how to use visualization techniques to better understand machine learning and deep learning models.
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Interpretable Machine Learning Products
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.
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Reactive Front-Ends with RxJS and Angular
Sergi Almar introduces the fundamentals of RxJS, explaining how to manage data streams like UI events, async HTTP requests, and WebSockets / SSE in a uniform way.
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Machine Intelligence at Google Scale
Guillaume LaForge presents pre-trained ML services such as Cloud Vision API and Speech API that works without any training, introducing Cloud AutoML.
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Fuelling the AI Revolution with Gaming
Alison Lowndes talks about the HW & SW that comprise NVIDIA's GPU computing platform for AI, across PC to data center, cloud to edge, training to inference.
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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.
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AI Panel
Panelists attempt to demystify AI and answer questions from the public.
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