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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
Anubhav Singh (author), Rimjhim Bhadani (author)
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| 자료유형 | E-BOOK |
|---|---|
| 서명/저자사항 | Mobile 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). |
| 개인저자 | Anubhav Singh (author), Rimjhim Bhadani (author). |
| 판사항 | 1st edition. |
| 발행사항 | Packt Publishing, 2020. |
| 형태사항 | 1 online resource. |
| 기타형태 저록 | Print version : 9781789611212 |
| ISBN | 9781789613995 178961399X |
| 내용주기 | Cover -- 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 |
| 요약 | Deep 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. |
| 일반주제명 | Machine learning. Mobile computing. Machine learning Mobile computing |
| 언어 | 영어 |
| 바로가기 | URL |
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