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2. fast.ai - Wikipedia

   en.wikipedia.org/wiki/Fast.ai

   fast.ai is a non-profit research group focused on deep learning and artificial intelligence. It was founded in 2016 by Jeremy Howard and Rachel Thomas with the goal of democratizing deep learning. [ 1 ]

3. Jeremy Howard (entrepreneur) - Wikipedia

   en.wikipedia.org/wiki/Jeremy_Howard_(entrepreneur)

   Jeremy Howard (born 13 November 1973) is an Australian data scientist, entrepreneur, and educator. [1]He is the co-founder of fast.ai, where he teaches introductory courses, [2] develops software, and conducts research in the area of deep learning.

4. Transformer (deep learning architecture) - Wikipedia

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

   For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

5. Attention (machine learning) - Wikipedia

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

   During the deep learning era, attention mechanism was developed to solve similar problems in encoding-decoding. [1]In machine translation, the seq2seq model, as it was proposed in 2014, [24] would encode an input text into a fixed-length vector, which would then be decoded into an output text.

6. Fast Artificial Neural Network - Wikipedia

   en.wikipedia.org/wiki/Fast_Artificial_Neural_Network

   The library has been used for research in image recognition, machine learning, biology, genetics, aerospace engineering, environmental sciences and artificial intelligence. Notable publications that cite FANN include: Papa, J. P. (2009). "Supervised pattern classification based on optimum-path forest".

7. Comparison of deep learning software - Wikipedia

   en.wikipedia.org/wiki/Comparison_of_deep...

   MATLAB + Deep Learning Toolbox (formally Neural Network Toolbox) MathWorks: 1992 Proprietary: No Linux, macOS, Windows: C, C++, Java, MATLAB: MATLAB: No No Train with Parallel Computing Toolbox and generate CUDA code with GPU Coder [23] No Yes [24] Yes [25] [26] Yes [25] Yes [25] Yes With Parallel Computing Toolbox [27] Yes Microsoft Cognitive ...

8. Convolutional neural network - Wikipedia

   en.wikipedia.org/wiki/Convolutional_neural_network

   A convolutional neural network (CNN) is a regularized type of feedforward neural network that learns features by itself via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different types of data including text, images and audio. [1]

9. Region Based Convolutional Neural Networks - Wikipedia

   en.wikipedia.org/wiki/Region_Based_Convolutional...

   Region-based Convolutional Neural Networks (R-CNN) are a family of machine learning models for computer vision, and specifically object detection and localization. [1] The original goal of R-CNN was to take an input image and produce a set of bounding boxes as output, where each bounding box contains an object and also the category (e.g. car or ...