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Chollet is the author of Xception: Deep Learning with Depthwise Separable Convolutions, [10] which is among the top ten most cited papers in CVPR proceedings at more than 18,000 citations. [11] Chollet is the author of the book Deep Learning with Python, [12] which sold over 100,000 copies, and the co-author with Joseph J. Allaire of Deep ...
Designed to enable fast experimentation with deep neural networks, Keras focuses on being user-friendly, modular, and extensible. It was developed as part of the research effort of project ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System), [ 5 ] and its primary author and maintainer is François Chollet , a Google engineer.
Python: Python: Only on Linux No Yes No Yes Yes Keras: François Chollet 2015 MIT license: Yes Linux, macOS, Windows: Python: Python, R: Only if using Theano as backend Can use Theano, Tensorflow or PlaidML as backends Yes No Yes Yes [20] Yes Yes No [21] Yes [22] Yes MATLAB + Deep Learning Toolbox (formally Neural Network Toolbox) MathWorks ...
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
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François Chollet: Keras: Deep learning framework [8] Evan Czaplicki Elm: Front-end web programming language [9] [10] Laurent Destailleur Dolibarr ERP CRM: Software suite for Enterprise Resource Planning and Customer Relationship Management [11] David Heinemeier Hansson: Ruby on Rails: Web framework [12] Rich Hickey: Clojure: Programming ...
A pizza delivery driver in Birmingham, Alabama, was fatally shot while making a stop on New Year's night, police said. Birmingham police received a call around 9 p.m. on Tuesday after receiving ...
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]
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