Machine Learning for Mobile: Empowering mobiles with the Artificial Intelligence capabilities using TensorFlow, Core ML and Caffe2Go
Revathi Gopalakrishnan, Avinash Venkateswarlu
Embark smartphones with smart and innovative mobile applications using the power of Machine Learning
- Practical understanding of machine learning concept and algorithms like clustering, classification, regression with thorough use-cases
- End-to-end coverage of on-device implementation of mobile ML applications using popular Core ML and TensorFlow Lite libraries
- Grasp all about machine learning and build smart mobile application across Android and iOS devices.
Machine Learning, represents an ultimate new era in software development enabling computers, mobiles and other devices to complete critical tasks without any special programming, thus allowing smartphones to produce an enormous amount useful data that can be mined analyzed and used to make predictions in the field of machine learning. This book will help you with how to deal with machine learning on mobile with easy to follow practical examples.
The book begins with giving you an introduction to machine learning on mobile and provides useful insights to be comfortable with the subject. You will then dive deep into supervised and unsupervised learning on mobile. Within this section, the book would cover important machine learning tools for mobile devices such as clustering, classification, regression followed by popular algorithms - Naive Bayes and Logistic Regression. You will also get to learn how to build a machine learning model using mobile-based libraries such as CoreML, Caffe2Go, Tensorflow lite and Weka on Android and iOS platform using SDKs. Next, you get to understand machine learning on cloud and how cloud services for machine learning are used in mobiles. Finally, the book would also cover an experiment on performing on-device image classification using mobile-based Tensorflow Lite and caffe2Go framework helping you to get a thorough understanding in building an artificial intelligence engine that runs directly on mobile devices.
By the end of this book, you would get a thorough understanding of machine learning models, performing on-device machine learning thereby enabling you to run artificial intelligence in real-time on mobile devices.
What you will learn
- Understand the tools such as CoreML, Caffe2Go, Tensorflow lite and Weka and libraries available to carry out mobile machine learning.
- Demystify supervised learning with classification and regression on mobile.
- Learn unsupervised learning on Android and iOS using k-means clustering and association algorithms.
- Perform practical exercises of building image classification using tensorflow lite and caffe2go
- Explore Cloud services for machine learning that can be used in mobile apps.
Who This Book Is For
The book is intended for mobile developers and machine learning users who are aspiring to take machine learning forward to mobiles and smart devices. Basic knowledge of machine learning and entry-level experience in mobile application development is preferred.