Machine Learning for Mobile: Empowering mobiles with the Artificial Intelligence capabilities using TensorFlow, Core ML and Caffe2Go

Embark smartphones with smart and innovative mobile applications using the power of Machine Learning

Key Features

• 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.

Book Description

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.

使用機器學習的力量，為智能手機提供智能和創新的移動應用程式

主要特點:
- 實際理解機器學習概念和算法，如分群、分類、回歸，並提供詳細的使用案例
- 全面涵蓋使用流行的Core ML和TensorFlow Lite庫在設備上實現移動機器學習應用程式的端到端覆蓋範圍
- 掌握機器學習的所有知識，並在Android和iOS設備上構建智能移動應用程式

書籍描述:
機器學習代表著軟體開發的新時代，使得電腦、手機和其他設備能夠在沒有特殊編程的情況下完成關鍵任務，從而使智能手機能夠產生大量有用的數據，這些數據可以在機器學習領域進行挖掘、分析和預測。本書將通過易於理解的實際示例，幫助您處理移動機器學習。

本書首先介紹了移動機器學習的基礎知識，並提供了有關該主題的有用見解。然後，您將深入研究移動設備上的監督學習和非監督學習。在這一部分中，本書將涵蓋移動設備上的重要機器學習工具，如分群、分類、回歸，以及流行的算法-朴素貝葉斯和邏輯回歸。您還將學習如何使用基於移動設備的庫（如CoreML、Caffe2Go、TensorFlow Lite和Weka）在Android和iOS平台上構建機器學習模型。接下來，您將了解雲端上的機器學習以及如何在移動設備上使用雲端機器學習服務。最後，本書還將介紹使用基於移動設備的TensorFlow Lite和Caffe2Go框架進行設備內圖像分類的實驗，幫助您全面了解在移動設備上構建直接運行的人工智能引擎。

通過閱讀本書，您將全面了解機器學習模型，並實現設備內機器學習，從而使您能夠在移動設備上實時運行人工智能。

您將學到什麼:
- 了解CoreML、Caffe2Go、TensorFlow Lite和Weka等工具和庫，以進行移動機器學習
- 解密在移動設備上的監督學習，包括分類和回歸
- 學習在Android和iOS上使用k-means分群和關聯算法進行非監督學習
- 通過使用TensorFlow Lite和Caffe2Go構建圖像分類的實際練習
- 探索可用於移動應用程式的雲端機器學習服務

本書適合對移動開發和機器學習有興趣的開發人員和用戶。建議具備機器學習的基本知識和入門級移動應用程式開發經驗。