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  1. AI - C3.ai, Inc.

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  3. Comparison of raster-to-vector conversion software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_raster-to...

    Super Vectorizer Effectmatrix Ltd. 2013 2016 (version 1.6.6) $29.99 Proprietary: macOS AutoTrace: Martin Weber 1998 2024 (version 0.31.10) Free GPL-2.0-or-later: Cross-platform, POSIX (mainly Unix-like) VTracer: Tsang Hao Fung 2020 2022 (version 0.5.0) Free MIT: Cross-platform (command-line version) Browsers with WebAssembly support (web version)

  4. Vector Institute (Canada) - Wikipedia

    en.wikipedia.org/wiki/Vector_Institute_(Canada)

    Purpose. Research in machine learning. Headquarters. Toronto, Ontario, Canada. Employees. 714 [1] Website. www .vectorinstitute .ai. The Vector Institute is a private, non-profit artificial intelligence research institute in Toronto focusing primarily on machine learning and deep learning research.

  5. Vector graphics - Wikipedia

    en.wikipedia.org/wiki/Vector_graphics

    Vector graphics are commonly found today in the SVG, WMF, EPS, PDF, CDR or AI types of graphic file formats, and are intrinsically different from the more common raster graphics file formats such as JPEG, PNG, APNG, GIF, WebP, BMP and MPEG4.

  6. tf–idf - Wikipedia

    en.wikipedia.org/wiki/Tf–idf

    tf–idf. In information retrieval, tf–idf (also TF*IDF, TFIDF, TF–IDF, or Tf–idf ), short for term frequency–inverse document frequency, is a measure of importance of a word to a document in a collection or corpus, adjusted for the fact that some words appear more frequently in general. [1]

  7. Image tracing - Wikipedia

    en.wikipedia.org/wiki/Image_tracing

    Common vector formats are SVG, DXF, EPS, EMF and AI. Vectorization can be used to update images or recover work. Personal computers often come with a simple paint program that produces a bitmap output file. These programs allow users to make simple illustrations by adding text, drawing outlines, and filling outlines with a specific color.

  8. Feature hashing - Wikipedia

    en.wikipedia.org/wiki/Feature_hashing

    function hashing_vectorizer(features : array of string, N : integer): x := new vector[N] for f in features: h := hash(f) x[h mod N] += 1 return x. Thus, if our feature vector is ["cat","dog","cat"] and hash function is if is "cat" and if is "dog". Let us take the output feature vector dimension ( N) to be 4.