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AI, ML & Data Engineering AI, ML & Data Engineering Follow 995 Followers
Natural Language Processing with Java - Second Edition: Book Review and Interview
Natural Language Processing with Java - Second Edition book covers the Natural Language Processing (NLP) topic and various tools developers can use in their applications. Technologies discussed in the book include Apache OpenNLP and Stanford NLP. InfoQ spoke with co-author Richard Reese about the book and how NLP can be used in enterprise applications.
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Development Development Follow 686 Followers
The 2018 InfoQ Editors’ Recommended Reading List: Part One
As part of our core values of sharing knowledge, the InfoQ editor team has listed and commented on their most recent recommended reading.
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AI, ML & Data Engineering AI, ML & Data Engineering Follow 995 Followers
Democratizing Stream Processing with Apache Kafka® and KSQL - Part 2
In this article, author Robin Moffatt shows how to use Apache Kafka and KSQL to build data integration and processing applications with the help of an e-commerce sample application. Three use cases discussed: customer operations, operational dashboard, and ad-hoc analytics.
How to Choose a Stream Processor for Your App
Analyzing and Preventing Unconscious Bias in Machine Learning
This article is based on Rachel Thomas’s keynote presentation, “Analyzing & Preventing Unconscious Bias in Machine Learning” at QCon.ai 2018. Thomas talks about the risks of machine learning bias.
Key Takeaway Points and Lessons Learned from QCon New York 2018
This year, at the seventh annual QCon New York, our second year in Time Square, we had in total 143 speakers across the 117 sessions, workshops, AMAs, Open Spaces and mini-workshops.
Understanding Software System Behaviour with ML and Time Series Data
David Andrzejewski presented "Understanding Software System Behavior with ML and Time Series Data". This article is a summary of his presentation and an overview on what to look out for.
Data Citizens: Why We All Care about Data Ethics
Data citizens are impacted by the models, methods, and algorithms created by data scientists, but they have limited agency to affect the tools which are acting on them.
Can People Trust the Automated Decisions Made by Algorithms?
The use of automated decision making is increasing. Algorithms can produce incomprehensible or socially undesirable results. Can we determine the safety of devices if we cannot understand them?
Democratizing Stream Processing with Apache Kafka and KSQL - Part 1
Columnar Databases and Vectorization
In this article, author Siddharth Teotia discusses the Dremio database which is based on Apache Arrow with vectorization capabilities.
Back to the Future: Demystifying Hindsight Bias
Are you planning to use artificial intelligence to solve enterprise problems? There is growing confirmation that you will need to address hindsight bias (aka label leakage) issue with your input data.
