Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mobile Artificial Intelligence Projects

You're reading from   Mobile Artificial Intelligence Projects Develop seven projects on your smartphone using artificial intelligence and deep learning techniques

Arrow left icon
Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789344073
Length 312 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Arun Padmanabhan Arun Padmanabhan
Author Profile Icon Arun Padmanabhan
Arun Padmanabhan
Karthikeyan NG Karthikeyan NG
Author Profile Icon Karthikeyan NG
Karthikeyan NG
Matt Cole Matt Cole
Author Profile Icon Matt Cole
Matt Cole
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Artificial Intelligence Concepts and Fundamentals FREE CHAPTER 2. Creating a Real-Estate Price Prediction Mobile App 3. Implementing Deep Net Architectures to Recognize Handwritten Digits 4. Building a Machine Vision Mobile App to Classify Flower Species 5. Building an ML Model to Predict Car Damage Using TensorFlow 6. PyTorch Experiments on NLP and RNN 7. TensorFlow on Mobile with Speech-to-Text with the WaveNet Model 8. Implementing GANs to Recognize Handwritten Digits 9. Sentiment Analysis over Text Using LinearSVC 10. What is Next? 11. Other Books You May Enjoy

Building a feedforward neural network to recognize handwritten digits, version one

In this section, we will use the knowledge that we gained from the last two chapters to tackle a problem that has unstructured data – image classification. The idea is to take a dive into solving a Computer Vision task with the current setup and the basics of neural networks that we are familiar with. We have seen that feedforward neural networks can be used for prediction using structured data; let's try that on images to classify handwritten digits.

To solve this task, we are going to leverage the MNSIT database and use the handwritten digits dataset. MNSIT stands for Modified National Institute of Standards and Technology. It is a large database that's commonly used for training, testing, and benchmarking image-related tasks in Computer Vision.

The MNSIT digits dataset contains...

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 $19.99/month. Cancel anytime
Banner background image