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  2. Freepik - Wikipedia

    en.wikipedia.org/wiki/Freepik

    Website. www .freepik .com. Freepik (stylized as FREEP!K) is an image bank website. Content produced and distributed by the online platform includes photographs, illustrations and vector images. The platform distributes its content under a freemium model, which means that users can access much of the content for free, but it is also possible to ...

  3. Pixabay - Wikipedia

    en.wikipedia.org/wiki/Pixabay

    Pixabay.com is a free stock photography and royalty-free stock media website. It is used for sharing photos, illustrations, vector graphics, film footage, music and sound effects, exclusively under the custom Pixabay license, which generally allows the free use of the material with some restrictions. [1] [2] [3]

  4. Euclidean vector - Wikipedia

    en.wikipedia.org/wiki/Euclidean_vector

    A vector pointing from A to B. In mathematics, physics, and engineering, a Euclidean vector or simply a vector (sometimes called a geometric vector or spatial vector) is a geometric object that has magnitude (or length) and direction. Euclidean vectors can be added and scaled to form a vector space.

  5. Alludo - Wikipedia

    en.wikipedia.org/wiki/Alludo

    In August 2003, Corel was bought out by the private equity firm Vector Capital for $1.05 a share (slightly more than the cash in the company). The company was voluntarily delisted from the NASDAQ and Toronto Stock Exchanges. Some U.S. shareholders alleged the management benefited from the buyout personally while the buyout price was too low.

  6. Rotation matrix - Wikipedia

    en.wikipedia.org/wiki/Rotation_matrix

    The matrix–vector product becomes a cross product of a vector with itself, ensuring that the result is zero: ( R − R T ) u = [ u ] × u = u × u = 0 {\displaystyle \left(R-R^{\mathsf {T}}\right)\mathbf {u} =[\mathbf {u} ]_{\times }\mathbf {u} =\mathbf {u} \times \mathbf {u} =0\,}

  7. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    In machine learning, support vector machines ( SVMs, also support vector networks [1]) are supervised max-margin models with associated learning algorithms that analyze data for classification and regression analysis.