Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Codeless Deep Learning with KNIME

You're reading from   Codeless Deep Learning with KNIME Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform

Arrow left icon
Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781800566613
Length 384 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Kathrin Melcher Kathrin Melcher
Author Profile Icon Kathrin Melcher
Kathrin Melcher
KNIME AG KNIME AG
Author Profile Icon KNIME AG
KNIME AG
Rosaria Silipo Rosaria Silipo
Author Profile Icon Rosaria Silipo
Rosaria Silipo
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Feedforward Neural Networks and KNIME Deep Learning Extension
2. Chapter 1: Introduction to Deep Learning with KNIME Analytics Platform FREE CHAPTER 3. Chapter 2: Data Access and Preprocessing with KNIME Analytics Platform 4. Chapter 3: Getting Started with Neural Networks 5. Chapter 4: Building and Training a Feedforward Neural Network 6. Section 2: Deep Learning Networks
7. Chapter 5: Autoencoder for Fraud Detection 8. Chapter 6: Recurrent Neural Networks for Demand Prediction 9. Chapter 7: Implementing NLP Applications 10. Chapter 8: Neural Machine Translation 11. Chapter 9: Convolutional Neural Networks for Image Classification 12. Section 3: Deployment and Productionizing
13. Chapter 10: Deploying a Deep Learning Network 14. Chapter 11: Best Practices and Other Deployment Options 15. Other Books You May Enjoy

Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Hands-On Mathematics for Deep Learning

Jay Dawani

ISBN: 978-1-83864-729-2

  • Understand the key mathematical concepts for building neural network models
  • Discover core multivariable calculus concepts
  • Improve the performance of deep learning models using optimization techniques
  • Cover optimization algorithms, from basic stochastic gradient descent (SGD) to the advanced Adam optimizer
  • Understand computational graphs and their importance in DL

Applied Deep Learning and Computer Vision for Self-Driving Cars

Sumit Ranjan, Dr. S. Senthamilarasu

ISBN: 978-1-83864-630-1

  • Implement deep neural network from scratch using the Keras library
  • Understand the importance of deep learning in self-driving cars
  • Get to grips with feature extraction techniques in image processing using the OpenCV library
  • Design a software pipeline that...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime