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  2. Scalability testing - Wikipedia

    en.wikipedia.org/wiki/Scalability_testing

    Vertical scaling, also known as scaling up, is the process of replacing a component with a device that is generally more powerful or improved. For example, replacing a processor with a faster one. Horizontal scaling, also known as scaling out is setting up another server for example to run in parallel with the original so they share the workload.

  3. Comparison gallery of image scaling algorithms - Wikipedia

    en.wikipedia.org/wiki/Comparison_gallery_of...

    Simple Fourier based interpolation based on padding of the frequency domain with zero components (a smooth-window-based approach would reduce the ringing).Beside the good conservation of details, notable is the ringing and the circular bleeding of content from the left border to right border (and way around).

  4. Systems design - Wikipedia

    en.wikipedia.org/wiki/Systems_design

    For example, services like Google, Twitter, Facebook, Amazon, and Netflix exemplify large-scale distributed systems. Here are key considerations: Functional and non-functional requirements; Capacity estimation; Usage of relational and/or NoSQL databases; Vertical scaling, horizontal scaling, sharding; Load balancing; Primary-secondary ...

  5. Scalability - Wikipedia

    en.wikipedia.org/wiki/Scalability

    Scaling vertically (up/down) means adding resources to (or removing resources from) a single node, typically involving the addition of CPUs, memory or storage to a single computer. [ 7 ] Benefits to scale-up include avoiding increased management complexity, more sophisticated programming to allocate tasks among resources and handling issues ...

  6. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    Image scaling can be interpreted as a form of image resampling or image reconstruction from the view of the Nyquist sampling theorem.According to the theorem, downsampling to a smaller image from a higher-resolution original can only be carried out after applying a suitable 2D anti-aliasing filter to prevent aliasing artifacts.

  7. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Feature scaling is a method used to normalize the range of independent variables or features of data. In data processing , it is also known as data normalization and is generally performed during the data preprocessing step.

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  9. Lenticular printing - Wikipedia

    en.wikipedia.org/wiki/Lenticular_printing

    Here the distance between different angles of view is "medium", so that while both eyes usually see the same picture, moving a little bit switches to the next picture in the series. Two or more sequential images are used, with only small differences between each image and the next.

  1. Related searches difference between horizontal and vertical scaling facebook ads free certification

    scale out vs vertical scalingscale out vs vertical scale up