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

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

    OpenML: [494] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [495] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...

  3. Data analysis for fraud detection - Wikipedia

    en.wikipedia.org/wiki/Data_analysis_for_fraud...

    Bayesian learning neural network is implemented for credit card fraud detection, telecommunications fraud, auto claim fraud detection, and medical insurance fraud. [ 13 ] Hybrid knowledge/statistical-based systems, where expert knowledge is integrated with statistical power, use a series of data mining techniques for the purpose of detecting ...

  4. Deepfake - Wikipedia

    en.wikipedia.org/wiki/Deepfake

    It was the first system to fully automate this kind of facial reanimation, and it did so using machine learning techniques to make connections between the sounds produced by a video's subject and the shape of the subject's face. [30] Contemporary academic projects have focused on creating more realistic videos and on improving techniques.

  5. Synthetic media - Wikipedia

    en.wikipedia.org/wiki/Synthetic_media

    Synthetic media (also known as AI-generated media, [1] [2] media produced by generative AI, [3] personalized media, personalized content, [4] and colloquially as deepfakes [5]) is a catch-all term for the artificial production, manipulation, and modification of data and media by automated means, especially through the use of artificial intelligence algorithms, such as for the purpose of ...

  6. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

  7. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    The plain transformer architecture had difficulty converging. In the original paper [1] the authors recommended using learning rate warmup. That is, the learning rate should linearly scale up from 0 to maximal value for the first part of the training (usually recommended to be 2% of the total number of training steps), before decaying again.

  8. Audio deepfake - Wikipedia

    en.wikipedia.org/wiki/Audio_deepfake

    The audio deepfake detection task determines whether the given speech audio is real or fake. Recently, this has become a hot topic in the forensic research community, trying to keep up with the rapid evolution of counterfeiting techniques.

  9. Knowledge distillation - Wikipedia

    en.wikipedia.org/wiki/Knowledge_distillation

    In machine learning, knowledge distillation or model distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many models) have more knowledge capacity than small models, this capacity might not be fully utilized. It can be just as ...