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Mobile Deep Learning Projects : 8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps.

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자료유형E-Book
개인저자Anubhav Singh (author), Rimjhim Bhadani (author)
서명/저자사항Mobile Deep Learning Projects :8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps.Anubhav Singh (author), Rimjhim Bhadani (author).
판사항1st edition.
발행사항Packt Publishing, 2020.
형태사항1 online resource
소장본 주기OCLC control number change
ISBN9781789613995
178961399X

내용주기Cover -- Title Page -- Copyright and Credits -- About Packt -- Contributors -- Table of Contents -- Preface -- Chapter 01: Introduction to Deep Learning for Mobile -- Growth of AI-powered mobile devices -- Changes in hardware to support AI -- Why do mobile devices need to have AI chips? -- Improved user experience with AI on mobile devices -- Personalization -- Virtual assistants -- Facial recognition -- AI-powered cameras -- Predictive text -- Most popular mobile applications that use AI -- Netflix -- Seeing AI -- Allo -- English Language Speech Assistant -- Socratic
Understanding machine learning and deep learning -- Understanding machine learning -- Understanding deep learning -- The input layer -- The hidden layers -- The output layer -- The activation function -- Introducing some common deep learning architectures -- Convolutional neural networks -- Generative adversarial networks -- Recurrent neural networks -- Long short-term memory -- Introducing reinforcement learning and NLP -- Reinforcement learning -- NLP -- Methods of integrating AI on Android and iOS -- Firebase ML Kit -- Core ML -- Caffe2 -- TensorFlow -- Summary
Chapter 02: Mobile Vision -- Face Detection Using On-Device Models -- Technical requirements -- Introduction to image processing -- Understanding images -- Manipulating images -- Rotation -- Grayscale conversion -- Developing a face detection application using Flutter -- Adding the pub dependencies -- Building the application -- Creating the first screen -- Building the row title -- Building the row with button widgets -- Creating the whole user interface -- Creating the second screen -- Getting the image file -- Analyzing the image to detect faces -- Marking the detected faces
Displaying the final image on the screen -- Creating the final MaterialApp -- Summary -- Chapter 03: Chatbot Using Actions on Google -- Technical requirements -- Understanding the tools available for creating chatbots -- Wit.ai -- Dialogflow -- How does Dialogflow work? -- Creating a Dialogflow account -- Creating a Dialogflow agent -- Understanding the Dialogflow Console -- Creating an Intent and grabbing entities -- Creating your first action on Google -- Why would you want to build an action on Google? -- Creating Actions on a Google project -- Creating an integration to the Google Assistant
Implementing a Webhook -- Deploying a webhook to Cloud Functions for Firebase -- Creating an Action on Google release -- Creating the UI for the conversational application -- Creating the Text Controller -- Creating ChatMessage -- Integrating the Dialogflow agent -- Adding audio interactions with the assistant -- Adding the plugin -- Adding SpeechRecognition -- Adding the mic button -- Summary -- Chapter 04: Recognizing Plant Species -- Technical requirements -- Introducing image classification -- Understanding the project architecture -- Introducing the Cloud Vision API
요약Deep learning is rapidly becoming the most popular topic in the industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart AI assistant, augmented reality, and more.
일반주제명Machine learning.
Mobile computing.
Machine learning
Mobile computing
언어영어
기타형태 저록Print version :9781789611212
대출바로가기http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2432341

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