Implementing AI Systems
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9781484263853
Springer Nature
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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. What You’ll Learn 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 Who This Book Is For Primarily for managers, IT professionals and executives of mid-size and large companies wanting to implement AI in their organization.