
Ambuj Agrawal
Broschiertes Buch
No-Code Artificial Intelligence
The new way to build AI powered applications (English Edition)
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Furthermore, the book will show how to build Machine Learning models for a variety of use cases in image recognition, video object recognition, and data prediction.
Ambuj Agrawal is the founder of AICromo and has deep expertise in machine learning and no-code AI technologies. Mr. Agrawal has previously created ZappyAI developing open-source RPA (Robotic Process Automation) software's and AI solutions . He has been one of the youngest Speakers at the Money2020 Europe, Fin.Techsummit Europe, Future of Work Summit London and Automation Summit Paris on the topic "Automation and Future of Work". He has also served as the president of Imperial College Entrepreneurship Club and as an advisor at the Cocoon Networks. He has received numerous innovation awards from Citibank, Imperial College London, Ministry of Justice UK, Bristol University, among others. He is also one of the youngest recipients of the "Exceptional Talent Visa in Digital Technology" by the UK Government for expertise in Compiler Design and Machine Learning. His expertise in machine learning, deep learning, no-code AI tools and software development puts him in an ideal position to write this book
Produktbeschreibung
- Verlag: Amazon Digital Services LLC - Kdp
- Seitenzahl: 232
- Erscheinungstermin: 7. März 2023
- Englisch
- Abmessung: 239mm x 183mm x 14mm
- Gewicht: 420g
- ISBN-13: 9789355513496
- ISBN-10: 9355513496
- Artikelnr.: 67614739
Herstellerkennzeichnung
Libri GmbH
Europaallee 1
36244 Bad Hersfeld
gpsr@libri.de
The first chapter gives a very brief introduction to AI and describes the main types of machine learning algorithms. The other chapters never make any reference to these types of machine learning, so the introductory chapter is disconnected from the rest of the book.
Chapters 2 introduces the …
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The first chapter gives a very brief introduction to AI and describes the main types of machine learning algorithms. The other chapters never make any reference to these types of machine learning, so the introductory chapter is disconnected from the rest of the book.
Chapters 2 introduces the concept of no-code AI and describes a number of existing platforms.
Chapters 3 to 10 describe how to create machine learning models using platforms and tools such as Google AutoML, Amazon SageMaker Canvas and DataRobot. These chapters contain a lot of copy-and-paste text, i.e. text that is copied literally or almost literally to several chapters. The text that is unique to each chapter is therefore relatively limited, since a lot of the remaining space is taken up by screenshots and explanations of these screenshots. The text is marred by many linguistic errors, many of which are also copied from chapter to chapter.
The final chapter provides some pointers on "coded AI" using popular Python libraries.
This is a disappointing book. In fact, it is the worst IT book that I have read in over thirty years.
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