Deep learning with R for beginners : design neural network models in R 3.5 using TensorFlow, Keras, and MXNet /: design neural network models in R 3.5 using TensorFlow, Keras, and MXNet. (2019)

• Record Type: Book
• Further Information: Note: Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden) Liu, Pablo Maldonado.
• Authors: Hodnett, Mark; Wiley, Joshua F; Liu, Yuxi (Hayden); Maldonado, Pablo
• Contents: Table of ContentsGetting Started with Deep LearningTraining a Prediction ModelDeep Learning FundamentalsTraining Deep Prediction ModelsImage Classification Using Convolutional Neural NetworksTuning and Optimizing ModelsNatural Language Processing Using Deep LearningDeep Learning Models Using TensorFlow in RAnomaly Detection and Recommendation SystemsRunning Deep Learning Models in the CloudThe Next Level in Deep LearningHandwritten Digit Recognition Using Convolutional Neural NetworksTraffic Sign Recognition for Intelligent VehiclesFraud Detection with AutoencodersText Generation Using Recurrent Neural NetworksSentiment Analysis with Word Embeddings.
• Publisher Details: Birmingham : Packt Publishing
• Publication Date: 2019
• Extent: 1 online resource
• Subjects: 006.31; Machine learning; R (Computer program language)
• Languages: English
• ISBNs: 9781838647223
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.