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

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

    CSV and PDF Natural language processing, QnA 2021 The Atticus Project: Vietnamese Image Captioning Dataset (UIT-ViIC) Vietnamese Image Captioning Dataset 19,250 captions for 3,850 images CSV and PDF Natural language processing, Computer vision 2020 [112] Lam et al. Vietnamese Names annotated with Genders (UIT-ViNames)

  3. 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.

  4. BookCorpus - Wikipedia

    en.wikipedia.org/wiki/BookCorpus

    It was the main corpus used to train the initial GPT model by OpenAI, [2] and has been used as training data for other early large language models including Google's BERT. [3] The dataset consists of around 985 million words, and the books that comprise it span a range of genres, including romance, science fiction, and fantasy.

  5. Exponential family random graph models - Wikipedia

    en.wikipedia.org/wiki/Exponential_family_random...

    Exponential Random Graph Models (ERGMs) are a family of statistical models for analyzing data from social and other networks. [ 1 ] [ 2 ] Examples of networks examined using ERGM include knowledge networks, [ 3 ] organizational networks, [ 4 ] colleague networks, [ 5 ] social media networks, networks of scientific development, [ 6 ] and others.

  6. CIFAR-10 - Wikipedia

    en.wikipedia.org/wiki/CIFAR-10

    The CIFAR-10 dataset (Canadian Institute For Advanced Research) is a collection of images that are commonly used to train machine learning and computer vision algorithms. It is one of the most widely used datasets for machine learning research.

  7. SqueezeNet - Wikipedia

    en.wikipedia.org/wiki/SqueezeNet

    SqueezeNet was originally described in SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size. [1] AlexNet is a deep neural network that has 240 MB of parameters, and SqueezeNet has just 5 MB of parameters.

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    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. General regression neural network - Wikipedia

    en.wikipedia.org/wiki/General_regression_neural...

    GRNN has been implemented in many computer languages including MATLAB, [3] R- programming language, Python (programming language) and Node.js.. Neural networks (specifically Multi-layer Perceptron) can delineate non-linear patterns in data by combining with generalized linear models by considering distribution of outcomes (sightly different from original GRNN).