3,135 articles
Kafka Connect
Kafka Connect is Apache Kafka's open-source framework for streaming data between Kafka and external systems via source and sink connectors, running workers in standalone or distributed modes with offsets, configs, and status stored in Kafka topics.
Kafka Streams
Kafka Streams, the Apache Kafka Streams API, is a Java/Scala client library for stream processing with input and output in Kafka topics, no separate processing cluster, local RocksDB state stores backed by changelog topics, and exactly_once_v2 processing guarantees.
Kafka: The Definitive Guide
Kafka: The Definitive Guide is O'Reilly's practitioner book on Apache Kafka: first edition 2017 by Narkhede, Shapira, and Palino; second edition November 2021 by Shapira, Palino, Sivaram, and Petty.
Kaggle
Kaggle is an online platform for data science and machine learning founded by Anthony Goldbloom in April 2010, hosting prediction competitions, datasets, and notebooks, and acquired by Google in 2017.
Kappa architecture
Kappa architecture, proposed by Jay Kreps in 2014, processes all data as streams over a replayable immutable log such as Kafka, replacing Lambda's dual batch and speed pipelines with one codebase and log replay for reprocessing.
Karatsuba algorithm
The Karatsuba algorithm, also known as the Karatsuba-Ofman algorithm, is a divide-and-conquer method for multiplying large numbers faster than the schoolbook method, discovered in 1960 and published in 1962.
Karp's 21 NP-complete problems
Karp's 21 NP-complete problems are the decision problems shown to be NP-complete in Richard M. Karp's 1972 paper, which used twenty polynomial-time reductions from Boolean satisfiability to prove them all hard.
Karush–Kuhn–Tucker conditions
The Karush–Kuhn–Tucker conditions, or KKT conditions, are first-order necessary conditions for a local optimum of a nonlinear program with equality and inequality constraints, published by Kuhn and Tucker in 1951.
KDD process
The KDD process, or Knowledge Discovery in Databases, is a seven-step model for extracting useful knowledge from data, defined by Fayyad, Piatetsky-Shapiro, and Smyth in 1996.
Kedro
Kedro is an open-source Python framework from QuantumBlack (open sourced June 2019, LF AI & Data since 2022) for reproducible, modular data pipelines built from nodes, pipelines, and a Data Catalog.
KEGG
KEGG (Kyoto Encyclopedia of Genes and Genomes) is a bioinformatics database resource for interpreting genomes through manually drawn biological pathway maps, started in 1995 by Minoru Kanehisa at the University of Tokyo.
Kensho (company)
Kensho is an American AI company founded in 2013 in Cambridge, Massachusetts, acquired by S&P Global in 2018 to serve as its AI innovation hub.
Keras
Keras is an open-source deep learning API written in Python, created by François Chollet at Google and first released in 2015; it runs on JAX, TensorFlow, or PyTorch.
Kernel (image processing)
A kernel in image processing is a small matrix of coefficients slid across an image and combined with its pixels by convolution to produce each output pixel of the filtered result.
Kernel clustering
Kernel clustering is a family of clustering methods that groups data points by pairwise similarity with a kernel function, capturing non-linearly separable clusters that plain k-means misses.
Kernel method
Kernel methods, also called kernel machines, are machine learning algorithms that operate on a matrix of pairwise similarities, letting linear algorithms handle nonlinear patterns in high-dimensional feature spaces.
Kernel PCA
Kernel PCA, or kernel principal component analysis, is a nonlinear extension of PCA that uses the kernel trick, introduced by Schölkopf, Smola, and Müller in 1998.
Kernel ridge regression
Kernel ridge regression (KRR) is a nonlinear regression method that combines ridge regression with the kernel trick, yielding a closed-form predictor used in molecular property prediction and genomic prediction.
Kernel trick
The kernel trick is a machine learning technique that lets algorithms operate in high-dimensional feature spaces by replacing inner products with a kernel function, as in support vector machines.
Kernelization
Kernelization is a framework in parameterized complexity theory for analyzing provably efficient and provably effective data reduction for NP-hard problems, originating in the early 1990s.
Kestra (software)
Kestra is an open-source, Apache 2.0 orchestration platform in Java for data, AI, and infrastructure workflows, defined in YAML. First released February 2022; version 2.0 (September 2026) rebuilt the engine around gRPC workers and AI features.
Keyphrase extraction
Keyphrase extraction is a natural language processing method that identifies the small set of phrases best describing a document, returning a ranked list drawn from the text.
Keypoint detection
Keypoint detection is a computer vision method that identifies distinctive points of interest, such as corners, in an image so the same locations can be found again in other images.
Keyword extraction
Keyword extraction is a natural language processing method that automatically identifies the most representative words or phrases in a document, used for indexing, summarization, and information retrieval.
Keyword spotting
Keyword spotting is a speech processing method that detects specific spoken words or phrases in an audio stream, outputting a confidence score rather than a transcription.
Kinetics (dataset)
Kinetics is a family of large-scale video datasets for human action recognition created by Google DeepMind and first released in 2017, growing from 400 action classes to 700, with hundreds of thousands of 10-second YouTube clips.
KITTI
KITTI is a benchmark suite of real-world driving data for computer vision and autonomous driving research, released in 2012 from recordings made around Karlsruhe, Germany.
Knewton
Knewton is an American adaptive learning technology company founded in 2008 and headquartered in New York City, best known for Knewton Alta, its adaptive higher-education courseware platform.
KNIME
KNIME (Konstanz Information Miner) is a free, open-source analytics platform, developed at the University of Konstanz, where users build data science work as visual workflows of nodes.
Knitro
Knitro, also sold as Artelys Knitro, is a commercial library for nonlinear optimization that originated at Northwestern University in the 1990s under Jorge Nocedal and is now developed by Artelys.