Mobile Deep Learning Projects: 8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps.
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 A...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Packt Publishing
2020.
|
| Edition: | 1st edition. |
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | 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. |
| Physical Description: | 1 online resource |
| ISBN: | 9781789613995 178961399X |
Staff View
MARC
| LEADER | 00000cam a2200000Ma 4500 | ||
|---|---|---|---|
| 001 | ZDB-4-EBA-on1152206297 | ||
| 003 | OCoLC | ||
| 005 | 20250103110447.0 | ||
| 006 | m o d | | ||
| 007 | cr ||||||||||| | ||
| 008 | 200403s2020 enk o 000 0 eng d | ||
| 040 | |a UKAHL |b eng |c UKAHL |d UKMGB |d OCLCO |d OCLCF |d EBLCP |d N$T |d YDX |d OCLCO |d OCLCQ |d OCLCO |d TMA |d OCLCQ | ||
| 015 | |a GBC050041 |2 bnb | ||
| 016 | 7 | |a 019760715 |2 Uk | |
| 019 | |a 1149672025 |a 1150180359 | ||
| 020 | |a 9781789613995 |q (e-book) | ||
| 020 | |a 178961399X | ||
| 020 | |z 9781789611212 (pbk.) | ||
| 035 | |a (OCoLC)1152206297 |z (OCoLC)1149672025 |z (OCoLC)1150180359 | ||
| 037 | |a 9781789613995 |b Packt Publishing | ||
| 050 | 4 | |a QA76.76.A65 | |
| 082 | 7 | |a 006.31 |2 23 | |
| 049 | |a MAIN | ||
| 100 | 1 | |a Anubhav Singh (author), Rimjhim Bhadani (author) | |
| 245 | 1 | 0 | |a Mobile Deep Learning Projects |b 8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps. |c Anubhav Singh (author), Rimjhim Bhadani (author). |
| 250 | |a 1st edition. | ||
| 260 | |b Packt Publishing |c 2020. | ||
| 300 | |a 1 online resource | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a computer |2 rdamedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 505 | 0 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 520 | |a 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. | ||
| 650 | 0 | |a Machine learning. |0 http://id.loc.gov/authorities/subjects/sh85079324 | |
| 650 | 0 | |a Mobile computing. |0 http://id.loc.gov/authorities/subjects/sh95004596 | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Informatique mobile. | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Mobile computing |2 fast | |
| 776 | 0 | 8 | |i Print version : |z 9781789611212 |
| 966 | 4 | 0 | |l DE-862 |p ZDB-4-EBA |q FWS_PDA_EBA |u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2432341 |3 Volltext |
| 966 | 4 | 0 | |l DE-863 |p ZDB-4-EBA |q FWS_PDA_EBA |u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2432341 |3 Volltext |
| 938 | |a Askews and Holts Library Services |b ASKH |n AH37330066 | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL6166922 | ||
| 938 | |a EBSCOhost |b EBSC |n 2432341 | ||
| 938 | |a YBP Library Services |b YANK |n 301206429 | ||
| 994 | |a 92 |b GEBAY | ||
| 912 | |a ZDB-4-EBA | ||
| 049 | |a DE-862 | ||
| 049 | |a DE-863 | ||
Record in the Search Index
| DE-BY-FWS_katkey | ZDB-4-EBA-on1152206297 |
|---|---|
| _version_ | 1829095328081510400 |
| adam_text | |
| any_adam_object | |
| author | Anubhav Singh (author), Rimjhim Bhadani (author) |
| author_facet | Anubhav Singh (author), Rimjhim Bhadani (author) |
| author_role | |
| author_sort | Anubhav Singh (author), Rimjhim Bhadani (author) |
| author_variant | s a r b a a sarba sarbaa |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.76.A65 |
| callnumber-search | QA76.76.A65 |
| callnumber-sort | QA 276.76 A65 |
| callnumber-subject | QA - Mathematics |
| collection | ZDB-4-EBA |
| contents | 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 |
| ctrlnum | (OCoLC)1152206297 |
| dewey-full | 006.31 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.31 |
| dewey-search | 006.31 |
| dewey-sort | 16.31 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | 1st edition. |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>05262cam a2200565Ma 4500</leader><controlfield tag="001">ZDB-4-EBA-on1152206297</controlfield><controlfield tag="003">OCoLC</controlfield><controlfield tag="005">20250103110447.0</controlfield><controlfield tag="006">m o d | </controlfield><controlfield tag="007">cr |||||||||||</controlfield><controlfield tag="008">200403s2020 enk o 000 0 eng d</controlfield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">UKAHL</subfield><subfield code="b">eng</subfield><subfield code="c">UKAHL</subfield><subfield code="d">UKMGB</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCF</subfield><subfield code="d">EBLCP</subfield><subfield code="d">N$T</subfield><subfield code="d">YDX</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">OCLCO</subfield><subfield code="d">TMA</subfield><subfield code="d">OCLCQ</subfield></datafield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">GBC050041</subfield><subfield code="2">bnb</subfield></datafield><datafield tag="016" ind1="7" ind2=" "><subfield code="a">019760715</subfield><subfield code="2">Uk</subfield></datafield><datafield tag="019" ind1=" " ind2=" "><subfield code="a">1149672025</subfield><subfield code="a">1150180359</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781789613995</subfield><subfield code="q">(e-book)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">178961399X</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9781789611212 (pbk.)</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1152206297</subfield><subfield code="z">(OCoLC)1149672025</subfield><subfield code="z">(OCoLC)1150180359</subfield></datafield><datafield tag="037" ind1=" " ind2=" "><subfield code="a">9781789613995</subfield><subfield code="b">Packt Publishing</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA76.76.A65</subfield></datafield><datafield tag="082" ind1="7" ind2=" "><subfield code="a">006.31</subfield><subfield code="2">23</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">MAIN</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Anubhav Singh (author), Rimjhim Bhadani (author)</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mobile Deep Learning Projects</subfield><subfield code="b">8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps.</subfield><subfield code="c">Anubhav Singh (author), Rimjhim Bhadani (author).</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st edition.</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="b">Packt Publishing</subfield><subfield code="c">2020.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh85079324</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Mobile computing.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh95004596</subfield></datafield><datafield tag="650" ind1=" " ind2="6"><subfield code="a">Apprentissage automatique.</subfield></datafield><datafield tag="650" ind1=" " ind2="6"><subfield code="a">Informatique mobile.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Machine learning</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Mobile computing</subfield><subfield code="2">fast</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version :</subfield><subfield code="z">9781789611212</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-862</subfield><subfield code="p">ZDB-4-EBA</subfield><subfield code="q">FWS_PDA_EBA</subfield><subfield code="u">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2432341</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-863</subfield><subfield code="p">ZDB-4-EBA</subfield><subfield code="q">FWS_PDA_EBA</subfield><subfield code="u">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2432341</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">Askews and Holts Library Services</subfield><subfield code="b">ASKH</subfield><subfield code="n">AH37330066</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">ProQuest Ebook Central</subfield><subfield code="b">EBLB</subfield><subfield code="n">EBL6166922</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">EBSCOhost</subfield><subfield code="b">EBSC</subfield><subfield code="n">2432341</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">YBP Library Services</subfield><subfield code="b">YANK</subfield><subfield code="n">301206429</subfield></datafield><datafield tag="994" ind1=" " ind2=" "><subfield code="a">92</subfield><subfield code="b">GEBAY</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-4-EBA</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-862</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-863</subfield></datafield></record></collection> |
| id | ZDB-4-EBA-on1152206297 |
| illustrated | Not Illustrated |
| indexdate | 2025-04-11T08:47:16Z |
| institution | BVB |
| isbn | 9781789613995 178961399X |
| language | English |
| oclc_num | 1152206297 |
| open_access_boolean | |
| owner | MAIN DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 1 online resource |
| psigel | ZDB-4-EBA FWS_PDA_EBA ZDB-4-EBA |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Packt Publishing |
| record_format | marc |
| spelling | Anubhav Singh (author), Rimjhim Bhadani (author) 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). 1st edition. Packt Publishing 2020. 1 online resource text rdacontent computer rdamedia online resource rdacarrier 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 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. Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Mobile computing. http://id.loc.gov/authorities/subjects/sh95004596 Apprentissage automatique. Informatique mobile. Machine learning fast Mobile computing fast Print version : 9781789611212 |
| spellingShingle | Anubhav Singh (author), Rimjhim Bhadani (author) Mobile Deep Learning Projects 8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps. 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 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Mobile computing. http://id.loc.gov/authorities/subjects/sh95004596 Apprentissage automatique. Informatique mobile. Machine learning fast Mobile computing fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85079324 http://id.loc.gov/authorities/subjects/sh95004596 |
| title | Mobile Deep Learning Projects 8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps. |
| title_auth | Mobile Deep Learning Projects 8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps. |
| title_exact_search | Mobile Deep Learning Projects 8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps. |
| title_full | 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). |
| title_fullStr | 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). |
| title_full_unstemmed | 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). |
| title_short | Mobile Deep Learning Projects |
| title_sort | mobile deep learning projects 8 project guides to help you work through end to end neural network projects on cross platform apps |
| title_sub | 8 Project Guides to Help You Work Through End-to-End Neural Network Projects on Cross-Platform Apps. |
| topic | Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Mobile computing. http://id.loc.gov/authorities/subjects/sh95004596 Apprentissage automatique. Informatique mobile. Machine learning fast Mobile computing fast |
| topic_facet | Machine learning. Mobile computing. Apprentissage automatique. Informatique mobile. Machine learning Mobile computing |
| work_keys_str_mv | AT anubhavsinghauthorrimjhimbhadaniauthor mobiledeeplearningprojects8projectguidestohelpyouworkthroughendtoendneuralnetworkprojectsoncrossplatformapps |