Free shipping on all orders over $79* Limited Time Only
Track My Order
Help Centre
Likes
My Wish ListsLogin / Join
Booktopia
Australia's local bookstore
Get Free Shipping on orders over $79
Deep Learning with Keras : Beginner's Guide to Deep Learning with Keras - Frank Millstein

Deep Learning with Keras

Beginner's Guide to Deep Learning with Keras

By: Frank Millstein

eBook | 22 October 2019

At a Glance

eBook

$6.99

or 4 interest-free payments of $1.75 with

Instant Digital Delivery to your Kobo Reader App

This book will introduce you to various supervised and unsupervised deep learning algorithms like the multilayer perceptron, linear regression and other more advanced deep convolutional and recurrent neural networks. You will also learn about image processing, handwritten recognition, object recognition and much more.Furthermore, you will get familiar with recurrent neural networks like LSTM and GAN as you explore processing sequence data like time series, text, and audio.The book will definitely be your best companion on this great deep learning journey with Keras introducing you to the basics you need to know in order to take next steps and learn more advanced deep neural networks.

Here Is a Preview of What You'll Learn Here...

  • The difference between deep learning and machine learning
  • Deep neural networks
  • Convolutional neural networks
  • Building deep learning models with Keras
  • Multi-layer perceptron network models
  • Activation functions
  • Handwritten recognition using MNIST
  • Solving multi-class classification problems
  • Recurrent neural networks and sequence classification
  • And much more...

Get this book NOW and learn more about Deep Learning with Keras!

on

You Can Find This eBook In

Non-FictionComputing & I.T.Computer ScienceArtificial IntelligenceNeural Networks & Fuzzy SystemsComputer VisionComputer Programming & Software DevelopmentAlgorithms & Data StructuresHuman-Computer InteractionInformation Visualisation

More in Neural Networks & Fuzzy Systems

This product is categorised by