Neural networks with R : smart models using CNN, RNN, deep learning, and artificial intelligence principles

Neural networks with R : smart models using CNN, RNN, deep learning, and artificial intelligence principles

Enregistré dans:

Détails bibliographiques
Auteur principal:	Ciaburro, Giuseppe (19..-....). (Auteur)
Autres auteurs:	Venkateswaran, Balaji. (Auteur)
Support:	E-Book
Langue:	Anglais
Publié:	Birmingham : Packt Publishing, 2017.
Autres localisations:	Voir dans le Sudoc
Accès en ligne:	Accès à l'E-book

Documents similaires

Hands-On Neural Networks with Keras : Design and create neural networks using deep learning and artificial intelligence principles
par: Purkait, Niloy.
Publié: (2019)

Practical convulational neural networks : implement advanced deep learning models using Python
par: Sewak, Mohit (19..-..).
Publié: (2018)

Hands-On Neural Networks : Learn how to build and train your first neural network model using Python
par: De Marchi, Leonardo.
Publié: (2019)

Neural Network for Beginners : Build Deep Neural Networks and Develop Strong Fundamentals using Python's NumPy, and Matplotlib
par: Klaas, Sebastian.

Artificial neural networks for engineering applications
par: Alanis, Alma Y. (19..-....).
Publié: (2019)

Artificial Intelligence in the Age of Neural Networks and Brain Computing
par: Kozma, Robert B..
Publié: (2018)

Introduction to Neural Networks
par: Gurney, Kevin.

Neural Network Projects with Python : The ultimate guide to using Python to explore the true power of neural networks through six projects
par: Loy, James.
Publié: (2019)

Neural networks with Keras cookbook : over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots
par: Kishore Ayyadevara, V..
Publié: (2019)

Hands-On Graph Neural Networks Using Python : Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch
par: Labonne, Maxime.

Keras 2.x projects : 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras
par: Ciaburro, Giuseppe (19..-....).
Publié: (2018)

Neural Networks in Finance : Gaining Predictive Edge in the Market
par: McNelis, Paul D..
Publié: (2004)

Neural Network Modeling and Identification of Dynamical Systems
par: Tiumentsev, Yury.
Publié: (2019)

Neural Networks Modeling and Control : Applications for Unknown Nonlinear Delayed Systems in Discrete Time
par: Rios, Jorge D..
Publié: (2020)

Fuzzy neural networks for real time control applications : concepts, modeling and algorithms for fast learning
par: Kayacan, Erdal (19..-....).
Publié: (2015)

Neural network programming with TensorFlow
par: Ghotra, Manpreet Singh.
Publié: (2017)

Hands-on neural network programming with C# : add powerful neural network capabilities to your C# enterprise applications
par: Cole, Matt R..
Publié: (2018)

Recurrent neural networks with Python quick start guide : sequential learning and language modeling with TensorFlow
par: Kostadinov, Simeon.
Publié: (2018)

Python machine learning cookbook : over 100 recipes to progress from smart data analytics to deep learning using real-world datasets
par: Ciaburro, Giuseppe (19..-....).
Publié: (2019)

Hands-on convolutional neural networks with TensorFlow : solve computer vision problems with modeling in TensorFlow and Python
Publié: (2018)

Hands-On Neural Networks with TensorFlow 2.0 : Understand TensorFlow, from static graph to eager execution, and design neural networks
par: Galeone, Paolo.
Publié: (2019)

Neural Network Computer Vision with OpenCV 5 : Build computer vision solutions using Python and DNN module
par: Krishna Nuti, Gopi.

Modeling Neural Development
par: Van Ooyen, Arjen (19..-....).

Time Series Forecasting using Deep Learning : Combining PyTorch, RNN, TCN, and Deep Neural Network Models to Provide Production-Ready Prediction Solutions
par: Gridin, Ivan.

Hands-On Deep Learning with R : A practical guide to designing, building, and improving neural network models using R
par: Pawlus, Michael.
Publié: (2020)

Advanced Deep Learning with R : Become an expert at designing, building, and improving advanced neural network models using R
par: Rai, Bharatendra.
Publié: (2019)

R deep learning projects : master the techniques to design and develop neural network models in R
par: Liu, Yuxi (Hayden).
Publié: (2018)

Hands-on machine learning on Google cloud platform : implementing smart and efficient analytics using Cloud ML Engine
par: Ciaburro, Giuseppe (19..-....).
Publié: (2018)

Deep Learning with R for Beginners : Design neural network models in R 3.5 using TensorFlow, Keras, and MXNet
par: Hodnett, Mark.
Publié: (2019)

The deep learning with PyTorch workshop : build deep neural networks and artificial intelligence applications with PyTorch
par: Saleh, Hyatt.
Publié: (2020)

Handbook of neural computation
par: Samui, Pijush (19..-....).
Publié: (2017)

Deep Learning with R Cookbook : Over 45 unique recipes to delve into neural network techniques using R 3.5.x
par: Gupta, Swarna.
Publié: (2020)

Regression analysis with R : design and develop statistical nodes to identify unique relationships within data at scale
par: Ciaburro, Giuseppe (19..-....).
Publié: (2018)

Python deep learning projects : 9 projects demystifying neural network and deep learning models for building intelligent systems
par: Lamons, Matthew.
Publié: (2018)

Deep learning essentials : your hands-on guide to the fundamentals of deep learning and neural network modeling
par: Di, Wei.
Publié: (2018)

Hands-on transfer learning with Python : implement advanced deep learning and neural network models using TensorFlow and Keras
par: Sarkar, Dipanjan (19..-....).
Publié: (2018)

Deep Network Design for Medical Image Computing : Principles and Applications
par: Liao, Haofu.

Deep learning with PyTorch : a practical approach to building neural network models using PyTorch
par: Subramanian, Vishnu (19..-....).
Publié: (2018)

Deep learning : practical neural networks with Java
par: Sugomori, Yusuke.
Publié: (2017)

Deep Learning for Natural Language Processing : Solve your natural language processing problems with smart deep neural networks
par: Reddy Bokka, Karthiek.
Publié: (2019)

Université catholique de l'Ouest - Bibliothèques - 3 place André Leroy - BP10808 - 49008 ANGERS Cedex 1