Tom Taulli

Implementing AI Systems (eBook, PDF)

Transform Your Business in 6 Steps

• Format: PDF

Produktbeschreibung

AI is one of the fastest growing corners of the tech world. But there remains one big problem: many AI projects fail. The fact is that AI is unique among IT projects. The technology requires a different mindset, in terms of understanding probabilities, data structures and complex algorithms. There is also a need to deal with complex issues like ethics and privacy.

This is where Implementing AI Systems comes in. You'll learn the step-by-step process for successful implementations of AI, backed up with numerous case studies from top companies. This book puts everything you need to know into one place - that is, it's the handbook you need for AI. You'll focus primarily on understanding the core concepts for AI like NLP, Machine Learning, Deep Learning and so on.

This book will help you find the right areas to apply AI.

You will:

• Put together an effective data strategy
• Create models and how to successfully test them
• Evaluate AI tools
• Assemble the right team
• Scale AI across an organization

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Produktdetails

• Verlag: Apress
• Seitenzahl: 196
• Erscheinungstermin: 11. Dezember 2020
• Englisch
• ISBN-13: 9781484263853
• Artikelnr.: 62300360

Autorenporträt

Tom Taulli has been developing software since the 1980s. In college, he started his first company, which focused on the development of e-learning systems. He created other companies as well, including Hypermart.net that was sold to InfoSpace in 1996. Along the way, Tom has written columns for online publications such as BusinessWeek.com, TechWeb.com, and Bloomberg.com. He also writes posts on Artificial Intelligence for Forbes.com and is the adviser to various companies in the space. You can reach Tom on Twitter (@ttaulli) or through his website (Taulli.com) where he has an online course on AI.

Inhaltsangabe

Chapter 1: AI Landscape.- Chapter 2: AI Foundations.- Chapter 3: Identify the Problem to be Solved.- Chapter 4: The Team.- Chapter 5: Data Preparation.- Chapter 6: Creating the Model.- Chapter 7: Deployment and Monitoring.- Chapter 8: Responsible AI.- Chapter 9: The Future of AI.- Glossary.