Information about Test

  1. Support vector machine

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    for Multiclass Support Vector Machines" (PDF). IEEE Transactions on Neural Networks. 13 (2): 415–25. doi:10.1109/72.991427. PMID 18244442. Platt, John;

  2. Data science

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    Artificial neural network Autoencoder Deep learning DeepDream Multilayer perceptron RNN LSTM GRU Restricted Boltzmann machine GAN SOM Convolutional neural network

  3. SpaCy

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    learning library Thinc. Using Thinc as its backend, spaCy features convolutional neural network models for part-of-speech tagging, dependency parsing, text categorization

  4. Reinforcement learning

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    for reinforcement learning in neural networks". Proceedings of the IEEE First International Conference on Neural Networks. CiteSeerX 10.1.1.129.8871.CS1

  5. Ilya Sutskever

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    He is the co-inventor with Alexander Krizhevsky of AlexNet, a convolutional neural network. He invented Sequence to Sequence Learning, together with Oriol

  6. Supervised learning

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    Geman, E. Bienenstock, and R. Doursat (1992). Neural networks and the bias/variance dilemma. Neural Computation 4, 1–58. G. James (2003) Variance and

  7. Conference on Neural Information Processing Systems

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    in 1986 as NIPS at the annual invitation-only Snowbird Meeting on Neural Networks for Computing organized by The California Institute of Technology and

  8. Machine learning in video games

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    and run on. Convolutional neural networks (CNN) are specialized ANNs that are often used to analyze image data. These types of networks are able to learn

  9. Convolutional deep belief network

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    science, a convolutional deep belief network (CDBN) is a type of deep artificial neural network composed of multiple layers of convolutional restricted

  10. EEG analysis

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    Dynamical system Chaos theory Artificial neural network Deep learning Convolutional neural network Recurrent neural network Machine learning Artificial intelligence

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