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

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

Enregistré dans:

Détails bibliographiques
Auteur principal:	Klaas, Sebastian. (Auteur)
Support:	E-Book
Langue:	Anglais
Publié:	New Delhi : BPB Publications.
Autres localisations:	Voir dans le Sudoc
Accès en ligne:	Accès à l'E-book

Documents similaires

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

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)

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)

Introduction to Neural Networks
par: Gurney, Kevin.

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

Neural networks with R : smart models using CNN, RNN, deep learning, and artificial intelligence principles
par: Ciaburro, Giuseppe (19..-....).
Publié: (2017)

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

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

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)

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

NumPy beginner's guide (Second Edition)
par: Idris, Ivan.
Publié: (2013)

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

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

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)

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

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)

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

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

NumPy : beginner's guide
par: Idris, Ivan.
Publié: (2015)

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

Hands-On Generative Adversarial Networks with PyTorch 1.x : Implement next-generation neural networks to build powerful GAN models using Python
par: Hany, John.
Publié: (2019)

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

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

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

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

Learning Python Networking : A complete guide to build and deploy strong networking capabilities using Python 3.7 and Ansible
par: Ortega, Jose Manuel.
Publié: (2019)

NumPy essentials
par: Chin, Leo (Liang-Huan).
Publié: (2016)

Data Analysis with Python : Introducing NumPy, Pandas, Matplotlib, and Essential Elements of Python Programming (English Edition)
par: Dixit, Rituraj.
Publié: (2022)

Python 3 Image Processing : Learn Image Processing with Python 3, NumPy, Matplotlib, and Scikit-image
par: Pajankar, Ashwin.

Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow
Publié: (2019)

Learning NumPy Array
par: Idris, Ivan.
Publié: (2014)

NumPy cookbook : over 70 interesting recipes for learning the Python open source mathematical library, NumPy
par: Idris, Ivan.
Publié: (2012)

Deep learning with TensorFlow : explore neural networks and build intelligent systems with Python
par: Zaccone, Giancarlo.
Publié: (2018)

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

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

Deep learning with PyTorch quick start guide : learn to train and deploy neural network models in Python
par: Julian, David.
Publié: (2018)

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

Networking Fundamentals : Develop the networking skills required to pass the Microsoft MTA Networking Fundamentals Exam 98-366
par: Davies, Gordon.
Publié: (2019)

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