-
AI, ML & Data Engineering AI, ML & Data Engineering Follow 873 Followers
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 pitfalls and risk the bias in machine learning brings to the decision-making process. She discusses three use cases of machine learning bias.
-
Development Development Follow 610 Followers
Key Takeaway Points and Lessons Learned from QCon New York 2018
This year, at the seventh annual QCon New York, we had in total 143 speakers across the 117 sessions, workshops, AMAs, Open Spaces and mini-workshops. Topics included containers and orchestration, machine learning, ethics, modern user interfaces, microservices, blockchain, empowered teams, modern Java, DevEX, Serverless, chaos and resilience, Go, Rust, Elixir, and security.
-
AI, ML & Data Engineering AI, ML & Data Engineering Follow 873 Followers
Understanding Software System Behaviour with ML and Time Series Data
David Andrzejewski presented "Understanding Software System Behaviour with ML and Time Series Data". This article is a summary of his presentation and an overview on what to look out for. Know about the traditional approaches to time series, how to handle missing values, and know about possibly occurring seasonality in your data. Be careful about what threshold you set for anomaly detection.
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
In this article, author discusses the stream processing with KSQL, the streaming SQL engine for Apache Kafka. Topics covered include challenges of stateful stream processing & how KSQL addresses them.
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.
Q&A on the Book Software Wasteland
In the book Software Wasteland Dave McComb explores what is causing application development waste and how visualizing the cost of change and becoming data-centric can help to reduce the waste.
Virtual Panel: Microservices Communication and Governance Using Service Mesh
Service mesh offers a platform to connect, manage, and secure microservices. InfoQ spoke with subject matter experts in this area to discuss service mesh frameworks.
Polyglot Persistence Powering Microservices
The Netflix cloud database engineering team provides several flavors of data persistence as a service to microservice development teams.
Migrating Batch ETL to Stream Processing: A Netflix Case Study with Kafka and Flink
At QCon NY, Shriya Arora presented “Personalising Netflix with Streaming Datasets” and discussed a migration of a data processing job from batch-style ETL to stream processing using Apache Flink.
