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Mobile Artificial Intelligence Projects

You're reading from  Mobile Artificial Intelligence Projects

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789344073
Pages 312 pages
Edition 1st Edition
Languages
Authors (3):
Karthikeyan NG Karthikeyan NG
Profile icon Karthikeyan NG
Arun Padmanabhan Arun Padmanabhan
Profile icon Arun Padmanabhan
Matt Cole Matt Cole
Profile icon Matt Cole
View More author details

Table of Contents (12) Chapters

Preface 1. Artificial Intelligence Concepts and Fundamentals 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

Popular ML–based cloud services

To begin your ML journey, you can use one of the existing cloud-based services on ML. ML as a Service (MLaaS) is widely used across all contemporary business sectors. Data is becoming cheaper, and data volume is growing exponentially. As a result, the processing power of devices is increasing at a much quicker rate. This trend has made way for multiple cloud-based services, such as Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), now joined by MLaaS.

Even though we can run an ML model on our mobile device, it is still greatly impacted by limited memory, CPU and Graphics Processing Unit (GPU) resources. In this case, a cloud service comes in handy.

Starting with ML in the cloud, there are multiple services available, such as facial recognition, optical character recognition, image recognition...

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