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AI, ML and Data Engineering InfoQ Trends Report - August 2021
How AI, ML and Data Engineering are evolving in 2021 as seen by the InfoQ editorial team. Topics discussed include deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML.
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Improving the Performance of a Route Editor Using a Quadtree
A quadtree is a tree data structure that allows the user to partition a two-dimensional space and to quickly find the intersection of objects. In this article we show how we used it to improve the performance of our route editor.
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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.
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Cats, Qubits, and Teleportation: The Spooky World of Quantum Algorithms (Part 2)
Quantum information theory really took off once people noticed that the computational complexity of quantum systems was actually a computational capacity, which could be applied to other problems, such as factorization, which is used within public key cryptography. This article explores quantum algorithms and their applicability.
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Big Data Processing Using Apache Spark - Part 6: Graph Data Analytics with Spark GraphX
In this article, author Srini Penchikala discusses Apache Spark GraphX library used for graph data processing and analytics. The article includes sample code for graph algorithms like PageRank, Connected Components and Triangle Counting.
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Spark GraphX in Action Book Review and Interview
“Spark GraphX in Action” book from Manning Publications, authored by Michael Malak and Robin East, provides a tutorial based coverage of Spark GraphX, the graph data processing library from Apache Spark framework. InfoQ spoke with authors about the book and Spark GraphX library as well as overall Spark framework and what's coming up in the area of graph data processing and analytics.
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Grokking Algorithms Review and Author Q&A
Manning’s Grokking Algorithms, written by Aditya Y. Bhargava, takes a novel approach to introducing such complex matters as data structures, algorithms, and complexity. Himself a visual learner, Bhargava explains he attempted to leverage the powerful expressiveness of illustration to make it easier to grasp topics that could be otherwise impenetrable for some.
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Beyond Data Mining
In this article, author talks about the need for a change in the predictive modeling community’s focus and compares the four types of data mining: algorithm mining, landscape mining, decision mining, and discussion mining.