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  2. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    Liulishuo, an online English learning platform, utilized TensorFlow to create an adaptive curriculum for each student. [79] TensorFlow was used to accurately assess a student's current abilities, and also helped decide the best future content to show based on those capabilities. [79]

  3. Tensor (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Tensor_(machine_learning)

    In machine learning, the term tensor informally refers to two different concepts (i) a way of organizing data and (ii) a multilinear (tensor) transformation. Data may be organized in a multidimensional array (M-way array), informally referred to as a "data tensor"; however, in the strict mathematical sense, a tensor is a multilinear mapping over a set of domain vector spaces to a range vector ...

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

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

    A dataset for NLP and climate change media researchers The dataset is made up of a number of data artifacts (JSON, JSONL & CSV text files & SQLite database) Climate news DB, Project's GitHub repository [394] ADGEfficiency Climatext Climatext is a dataset for sentence-based climate change topic detection. HF dataset [395] University of Zurich ...

  5. MNIST database - Wikipedia

    en.wikipedia.org/wiki/MNIST_database

    Extended MNIST (EMNIST) is a newer dataset developed and released by NIST to be the (final) successor to MNIST. [ 15 ] [ 16 ] MNIST included images only of handwritten digits. EMNIST includes all the images from NIST Special Database 19 (SD 19), which is a large database of 814,255 handwritten uppercase and lower case letters and digits.

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  7. Tensor Processing Unit - Wikipedia

    en.wikipedia.org/wiki/Tensor_Processing_Unit

    The machine learning runtime used to execute models on the Edge TPU is based on TensorFlow Lite. [47] The Edge TPU is only capable of accelerating forward-pass operations, which means it's primarily useful for performing inferences (although it is possible to perform lightweight transfer learning on the Edge TPU [ 48 ] ).

  8. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [70] [71] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.

  9. Inception (deep learning architecture) - Wikipedia

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

    Inception [1] is a family of convolutional neural network (CNN) for computer vision, introduced by researchers at Google in 2014 as GoogLeNet (later renamed Inception v1).). The series was historically important as an early CNN that separates the stem (data ingest), body (data processing), and head (prediction), an architectural design that persists in all modern