Enterprise AI in the Cloud: a practical guide to deploying end-to-end machine learning and ChatGPT solutions
Embrace emerging AI trends and integrate your operations with cutting-edge solutionsEnterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like gen...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, New Jersey
Wiley
[2024]
|
| Schriftenreihe: | Tech Today
|
| Schlagworte: | |
| Zusammenfassung: | Embrace emerging AI trends and integrate your operations with cutting-edge solutionsEnterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises.- You'll also discover best practices on optimizing cloud infrastructure for scalability and automation.Enterprise AI in the Cloud helps you gain a solid understanding of:* AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation* State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning* Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation* AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS,- and Google Cloud platforms* AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture* Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics* Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating ModelWhether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments.- |
| Beschreibung: | Develop and implement a custom, enterprise-wide AI solution with guidance from a renowned industry leaderIn Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions, digital platform strategist and architect Rabi Jay delivers a start-to-finish resource for professionals and companies who seek to implement new AI tech--including generative AI and machine learning (ML)--in their day-to-day operations.The ultimate go-to guide for setting up cloud AI platforms quickly and confidently, this book shows you how to start an enterprise-wide AI transformation effort, from ideation to implementation, with clearly defined processes, numerous examples, and hands-on exercises. The author offers expert guidance on cloud platform selection and integration, as well as best practices on optimizing cloud infrastructure for scalability and automation. He also provides review questions and answers at the end of each chapter to develop your understanding and improve retention of the discussed topics.Perfect for beginning and experienced AI and ML Operations engineers, Enterprise AI in the Cloud walks you through how to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise. |
| Beschreibung: | XX, 504 Seiten Illustrationen, Diagramme |
| ISBN: | 9781394213054 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV049639791 | ||
| 003 | DE-604 | ||
| 005 | 20240429 | ||
| 007 | t | ||
| 008 | 240408m20242023 a||| |||| 00||| eng d | ||
| 020 | |a 9781394213054 |9 978-1-394-21305-4 | ||
| 024 | 3 | |a 9781394213054 | |
| 035 | |a (ELiSA)ELiSA-9781394213054 | ||
| 035 | |a (OCoLC)1437852151 | ||
| 035 | |a (DE-599)HBZHT030644145 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-1049 | ||
| 084 | |a ST 300 |0 (DE-625)143649: |2 rvk | ||
| 100 | 1 | |a Jay, Rabi |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Enterprise AI in the Cloud |b a practical guide to deploying end-to-end machine learning and ChatGPT solutions |c Rabi Jay |
| 264 | 1 | |a Hoboken, New Jersey |b Wiley |c [2024] | |
| 264 | 4 | |c © 2024 | |
| 300 | |a XX, 504 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Tech Today | |
| 500 | |a Develop and implement a custom, enterprise-wide AI solution with guidance from a renowned industry leaderIn Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions, digital platform strategist and architect Rabi Jay delivers a start-to-finish resource for professionals and companies who seek to implement new AI tech--including generative AI and machine learning (ML)--in their day-to-day operations.The ultimate go-to guide for setting up cloud AI platforms quickly and confidently, this book shows you how to start an enterprise-wide AI transformation effort, from ideation to implementation, with clearly defined processes, numerous examples, and hands-on exercises. The author offers expert guidance on cloud platform selection and integration, as well as best practices on optimizing cloud infrastructure for scalability and automation. He also provides review questions and answers at the end of each chapter to develop your understanding and improve retention of the discussed topics.Perfect for beginning and experienced AI and ML Operations engineers, Enterprise AI in the Cloud walks you through how to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. | ||
| 500 | |a With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise. | ||
| 520 | |a Embrace emerging AI trends and integrate your operations with cutting-edge solutionsEnterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises.- | ||
| 520 | |a You'll also discover best practices on optimizing cloud infrastructure for scalability and automation.Enterprise AI in the Cloud helps you gain a solid understanding of:* AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation* State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning* Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation* AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS,- | ||
| 520 | |a and Google Cloud platforms* AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture* Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics* Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating ModelWhether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments.- | ||
| 653 | |a Künstliche Intelligenz | ||
| 653 | |a Software Engineering | ||
| 653 | |a Informatik | ||
| 653 | 0 | |a Artificial Intelligence | |
| 653 | 0 | |a Cloud | |
| 653 | 0 | |a Cloud Computing | |
| 653 | 0 | |a Computer Science | |
| 653 | 0 | |a Informatik | |
| 653 | 0 | |a KI | |
| 653 | 0 | |a Künstliche Intelligenz | |
| 653 | 0 | |a Software Engineering | |
| 653 | 0 | |a Software-Engineering | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe, epdf |z 9781394213078 |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe, epub |z 978-1-394-21306-1 |
Datensatz im Suchindex
| _version_ | 1805082109026500608 |
|---|---|
| adam_text | |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Jay, Rabi |
| author_facet | Jay, Rabi |
| author_role | aut |
| author_sort | Jay, Rabi |
| author_variant | r j rj |
| building | Verbundindex |
| bvnumber | BV049639791 |
| classification_rvk | ST 300 |
| ctrlnum | (ELiSA)ELiSA-9781394213054 (OCoLC)1437852151 (DE-599)HBZHT030644145 |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 c 4500</leader><controlfield tag="001">BV049639791</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20240429</controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">240408m20242023 a||| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781394213054</subfield><subfield code="9">978-1-394-21305-4</subfield></datafield><datafield tag="024" ind1="3" ind2=" "><subfield code="a">9781394213054</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELiSA)ELiSA-9781394213054</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1437852151</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)HBZHT030644145</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-1049</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 300</subfield><subfield code="0">(DE-625)143649:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Jay, Rabi</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Enterprise AI in the Cloud</subfield><subfield code="b">a practical guide to deploying end-to-end machine learning and ChatGPT solutions</subfield><subfield code="c">Rabi Jay</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hoboken, New Jersey</subfield><subfield code="b">Wiley</subfield><subfield code="c">[2024]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2024</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XX, 504 Seiten</subfield><subfield code="b">Illustrationen, Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Tech Today</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Develop and implement a custom, enterprise-wide AI solution with guidance from a renowned industry leaderIn Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions, digital platform strategist and architect Rabi Jay delivers a start-to-finish resource for professionals and companies who seek to implement new AI tech--including generative AI and machine learning (ML)--in their day-to-day operations.The ultimate go-to guide for setting up cloud AI platforms quickly and confidently, this book shows you how to start an enterprise-wide AI transformation effort, from ideation to implementation, with clearly defined processes, numerous examples, and hands-on exercises. The author offers expert guidance on cloud platform selection and integration, as well as best practices on optimizing cloud infrastructure for scalability and automation. He also provides review questions and answers at the end of each chapter to develop your understanding and improve retention of the discussed topics.Perfect for beginning and experienced AI and ML Operations engineers, Enterprise AI in the Cloud walks you through how to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments.</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Embrace emerging AI trends and integrate your operations with cutting-edge solutionsEnterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises.-</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">You'll also discover best practices on optimizing cloud infrastructure for scalability and automation.Enterprise AI in the Cloud helps you gain a solid understanding of:* AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation* State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning* Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation* AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS,-</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">and Google Cloud platforms* AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture* Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics* Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating ModelWhether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments.-</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Künstliche Intelligenz</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Software Engineering</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Informatik</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Artificial Intelligence</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Cloud</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Cloud Computing</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Computer Science</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Informatik</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">KI</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Künstliche Intelligenz</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Software Engineering</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Software-Engineering</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe, epdf</subfield><subfield code="z">9781394213078</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe, epub</subfield><subfield code="z">978-1-394-21306-1</subfield></datafield></record></collection> |
| id | DE-604.BV049639791 |
| illustrated | Illustrated |
| index_date | 2024-07-03T23:39:21Z |
| indexdate | 2024-07-20T07:27:26Z |
| institution | BVB |
| isbn | 9781394213054 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034983435 |
| oclc_num | 1437852151 |
| open_access_boolean | |
| owner | DE-1049 |
| owner_facet | DE-1049 |
| physical | XX, 504 Seiten Illustrationen, Diagramme |
| publishDate | 2024 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Wiley |
| record_format | marc |
| series2 | Tech Today |
| spelling | Jay, Rabi Verfasser aut Enterprise AI in the Cloud a practical guide to deploying end-to-end machine learning and ChatGPT solutions Rabi Jay Hoboken, New Jersey Wiley [2024] © 2024 XX, 504 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Tech Today Develop and implement a custom, enterprise-wide AI solution with guidance from a renowned industry leaderIn Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions, digital platform strategist and architect Rabi Jay delivers a start-to-finish resource for professionals and companies who seek to implement new AI tech--including generative AI and machine learning (ML)--in their day-to-day operations.The ultimate go-to guide for setting up cloud AI platforms quickly and confidently, this book shows you how to start an enterprise-wide AI transformation effort, from ideation to implementation, with clearly defined processes, numerous examples, and hands-on exercises. The author offers expert guidance on cloud platform selection and integration, as well as best practices on optimizing cloud infrastructure for scalability and automation. He also provides review questions and answers at the end of each chapter to develop your understanding and improve retention of the discussed topics.Perfect for beginning and experienced AI and ML Operations engineers, Enterprise AI in the Cloud walks you through how to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise. Embrace emerging AI trends and integrate your operations with cutting-edge solutionsEnterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises.- You'll also discover best practices on optimizing cloud infrastructure for scalability and automation.Enterprise AI in the Cloud helps you gain a solid understanding of:* AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation* State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning* Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation* AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS,- and Google Cloud platforms* AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture* Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics* Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating ModelWhether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments.- Künstliche Intelligenz Software Engineering Informatik Artificial Intelligence Cloud Cloud Computing Computer Science KI Software-Engineering Erscheint auch als Online-Ausgabe, epdf 9781394213078 Erscheint auch als Online-Ausgabe, epub 978-1-394-21306-1 |
| spellingShingle | Jay, Rabi Enterprise AI in the Cloud a practical guide to deploying end-to-end machine learning and ChatGPT solutions |
| title | Enterprise AI in the Cloud a practical guide to deploying end-to-end machine learning and ChatGPT solutions |
| title_auth | Enterprise AI in the Cloud a practical guide to deploying end-to-end machine learning and ChatGPT solutions |
| title_exact_search | Enterprise AI in the Cloud a practical guide to deploying end-to-end machine learning and ChatGPT solutions |
| title_exact_search_txtP | Enterprise AI in the Cloud a practical guide to deploying end-to-end machine learning and ChatGPT solutions |
| title_full | Enterprise AI in the Cloud a practical guide to deploying end-to-end machine learning and ChatGPT solutions Rabi Jay |
| title_fullStr | Enterprise AI in the Cloud a practical guide to deploying end-to-end machine learning and ChatGPT solutions Rabi Jay |
| title_full_unstemmed | Enterprise AI in the Cloud a practical guide to deploying end-to-end machine learning and ChatGPT solutions Rabi Jay |
| title_short | Enterprise AI in the Cloud |
| title_sort | enterprise ai in the cloud a practical guide to deploying end to end machine learning and chatgpt solutions |
| title_sub | a practical guide to deploying end-to-end machine learning and ChatGPT solutions |
| work_keys_str_mv | AT jayrabi enterpriseaiinthecloudapracticalguidetodeployingendtoendmachinelearningandchatgptsolutions |