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Book
Deep learning with Python
Author:
ISBN: 1617296864 9781617296864 Year: 2021 Publisher: Shelter Island, N.Y. Manning


Book
Economie, économistes
Authors: ---
ISBN: 2200921527 9782200921521 Year: 2006 Publisher: Paris: Armand Colin,

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France


Dissertation
De la pseudo-paralysie de Parrot
Author:
Year: 1895 Publisher: Bordeaux : Imprimerie et Lithographie Gagnebin,

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Book
Deep learning with R
Authors: ---
ISBN: 9781617295546 161729554X Year: 2018 Publisher: Shelter Island, N.Y. Manning

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Introduces deep learning systems using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples.

Keywords

Artificial intelligence. --- Computer vision. --- Machine learning --- Mathematical statistics --- Neural networks (Computer science). --- R (Computer program language). --- Technological innovations. --- Data processing. --- Artificial intelligence. Robotics. Simulation. Graphics --- Mathematical linguistics --- Neural networks (Computer science) --- R (Computer program language) --- Artificial intelligence --- Computer vision --- Programming Languages --- Artificial Intelligence --- Neural Networks, Computer --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Natural computation --- Soft computing --- GNU-S (Computer program language) --- Domain-specific programming languages --- Technological innovations --- Data processing --- Computational Neural Networks --- Connectionist Models --- Models, Neural Network --- Neural Network Models --- Neural Networks (Computer) --- Perceptrons --- Computational Neural Network --- Computer Neural Network --- Computer Neural Networks --- Connectionist Model --- Model, Connectionist --- Model, Neural Network --- Models, Connectionist --- Network Model, Neural --- Network Models, Neural --- Network, Computational Neural --- Network, Computer Neural --- Network, Neural (Computer) --- Networks, Computational Neural --- Networks, Computer Neural --- Networks, Neural (Computer) --- Neural Network (Computer) --- Neural Network Model --- Neural Network, Computational --- Neural Network, Computer --- Neural Networks, Computational --- Perceptron --- Computational Intelligence --- AI (Artificial Intelligence) --- Computer Reasoning --- Computer Vision Systems --- Knowledge Acquisition (Computer) --- Knowledge Representation (Computer) --- Machine Intelligence --- Acquisition, Knowledge (Computer) --- Computer Vision System --- Intelligence, Artificial --- Intelligence, Computational --- Intelligence, Machine --- Knowledge Representations (Computer) --- Reasoning, Computer --- Representation, Knowledge (Computer) --- System, Computer Vision --- Systems, Computer Vision --- Vision System, Computer --- Vision Systems, Computer --- Heuristics --- Language, Programming --- Languages, Programming --- Programming Language --- Machine vision --- Vision, Computer --- Image processing --- Pattern recognition systems --- Learning, Machine --- Machine theory --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- #SBIB:303H4 --- Informatica in de sociale wetenschappen


Book
Deep Learning with TensorFlow and Keras : Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models.
Authors: --- --- ---
ISBN: 1803245719 Year: 2022 Publisher: Birmingham : Packt Publishing, Limited,

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Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML.

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