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  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    GitHub repository of the project: Dynatrace This data is not pre-processed AIOps Challenge 2020 Data This data is not pre-processed GitHub repository of the project: Loghub This data is not pre-processed List of repositories: HTML Pages This data is not pre-processed List of HTML pages: Opensift ebooks This data is not pre-processed [410]

  3. Proximal policy optimization - Wikipedia

    en.wikipedia.org/wiki/Proximal_Policy_Optimization

    Sample efficiency indicates whether the algorithms need more or less data to train a good policy. PPO achieved sample efficiency because of its use of surrogate objectives. The surrogate objective allows PPO to avoid the new policy moving too far from the old policy; the clip function regularizes the policy update and reuses training data ...

  4. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics , statistics, computer science , information science , and domain knowledge . [ 6 ]

  5. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    [5] Data mining in customer relationship management applications can contribute significantly to the bottom line. [citation needed] Rather than randomly contacting a prospect or customer through a call center or sending mail, a company can concentrate its efforts on prospects that are predicted to have a high likelihood of responding to an ...

  6. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Stable Diffusion was trained on pairs of images and captions taken from LAION-5B, a publicly available dataset derived from Common Crawl data scraped from the web, where 5 billion image-text pairs were classified based on language and filtered into separate datasets by resolution, a predicted likelihood of containing a watermark, and predicted ...

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  8. Random sample consensus - Wikipedia

    en.wikipedia.org/wiki/Random_sample_consensus

    A simple example is fitting a line in two dimensions to a set of observations. Assuming that this set contains both inliers, i.e., points which approximately can be fitted to a line, and outliers, points which cannot be fitted to this line, a simple least squares method for line fitting will generally produce a line with a bad fit to the data including inliers and outliers.

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