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  2. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  3. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    TensorFlow serves as a core platform and library for machine learning. TensorFlow's APIs use Keras to allow users to make their own machine-learning models. [ 41] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving.

  4. Traffic collision avoidance system - Wikipedia

    en.wikipedia.org/wiki/Traffic_collision...

    A traffic alert and collision avoidance system ( TCAS, pronounced / tiːkæs /; TEE-kas ), is an aircraft collision avoidance system designed to reduce the incidence of mid-air collision (MAC) between aircraft. It monitors the airspace around an aircraft for other aircraft equipped with a corresponding active transponder, independent of air ...

  5. t-distributed stochastic neighbor embedding - Wikipedia

    en.wikipedia.org/wiki/T-distributed_stochastic...

    The R package Rtsne implements t-SNE in R. ELKI contains tSNE, also with Barnes-Hut approximation; scikit-learn, a popular machine learning library in Python implements t-SNE with both exact solutions and the Barnes-Hut approximation. Tensorboard, the visualization kit associated with TensorFlow, also implements t-SNE (online version)

  6. Transformer (deep learning architecture) - Wikipedia

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

    Machine learningand data mining. A standard Transformer architecture, showing on the left an encoder, and on the right a decoder. Note: it uses the pre-LN convention, which is different from the post-LN convention used in the original 2017 Transformer. A transformer is a deep learning architecture developed by researchers at Google and based on ...

  7. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    t. e. Machine learning ( ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data and thus perform tasks without explicit instructions. [ 1] Recently, artificial neural networks have been able to surpass many previous approaches ...

  8. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    Chainer: Fully in Python, production support for CPU, GPU, distributed training. Deeplearning4j: Deep learning in Java and Scala on multi-GPU-enabled Spark. Flux: includes interfaces for RNNs, including GRUs and LSTMs, written in Julia. Keras: High-level API, providing a wrapper to many other deep learning libraries. Microsoft Cognitive Toolkit

  9. Similarity learning - Wikipedia

    en.wikipedia.org/wiki/Similarity_learning

    Similarity learning. Similarity learning is an area of supervised machine learning in artificial intelligence. It is closely related to regression and classification, but the goal is to learn a similarity function that measures how similar or related two objects are. It has applications in ranking, in recommendation systems, visual identity ...