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  2. Databricks - Wikipedia

    en.wikipedia.org/wiki/Databricks

    Databricks, Inc. is a global data, analytics, and artificial intelligence (AI) company, founded in 2013 by the original creators of Apache Spark. [1] [4] The company provides a cloud-based platform to help enterprises build, scale, and govern data and AI, including generative AI and other machine learning models.

  3. Data build tool - Wikipedia

    en.wikipedia.org/wiki/Data_build_tool

    It started at RJMetrics in 2016 as a solution to add basic transformation capabilities to Stitch (acquired by Talend in 2018). [3] The earliest versions of dbt allowed analysts to contribute to the data transformation process following the best practices of software engineering.

  4. Vector database - Wikipedia

    en.wikipedia.org/wiki/Vector_database

    A vector database, vector store or vector search engine is a database that can store vectors (fixed-length lists of numbers) along with other data items. Vector databases typically implement one or more Approximate Nearest Neighbor algorithms, [1] [2] [3] so that one can search the database with a query vector to retrieve the closest matching database records.

  5. Ali Ghodsi - Wikipedia

    en.wikipedia.org/wiki/Ali_Ghodsi

    He is a co-founder and CEO of Databricks [5] [6] [7] and an adjunct professor at UC Berkeley. He coauthored several influential papers, including Apache Mesos [8] and Apache Spark SQL. [9] Ghodsi received his PhD from KTH Royal Institute of Technology in Sweden, advised by Seif Haridi. He was a co-founder of Peerialism AB, a Stockholm-based ...

  6. Block-matching algorithm - Wikipedia

    en.wikipedia.org/wiki/Block-matching_algorithm

    A Block Matching Algorithm is a way of locating matching macroblocks in a sequence of digital video frames for the purposes of motion estimation.The underlying supposition behind motion estimation is that the patterns corresponding to objects and background in a frame of video sequence move within the frame to form corresponding objects on the subsequent frame.

  7. Ranking SVM - Wikipedia

    en.wikipedia.org/wiki/Ranking_SVM

    In machine learning, a ranking SVM is a variant of the support vector machine algorithm, which is used to solve certain ranking problems (via learning to rank). The ranking SVM algorithm was published by Thorsten Joachims in 2002. [1] The original purpose of the algorithm was to improve the performance of an internet search engine.

  8. Dynamic pricing - Wikipedia

    en.wikipedia.org/wiki/Dynamic_pricing

    Cost-plus pricing is the most basic method of pricing. A store will simply charge consumers the cost required to produce a product plus a predetermined amount of profit. Cost-plus pricing is simple to execute, but it only considers internal information when setting the price and does not factor in external influencers like market reactions, the weather, or changes in consumer va

  9. Algorithmic pricing - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_pricing

    Algorithmic pricing is the practice of automatically setting the requested price for items for sale, in order to maximize the seller's profits. Dynamic pricing algorithms usually rely on one or more of the following data. Probabilistic and statistical information on potential buyers; see Bayesian-optimal pricing. Prices of competitors.

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