Deploying Machine Learning

Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Les mer
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(Paperback) Fri frakt!
Leveringstid: Ikke i salg

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Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn:

What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important
What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more
How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products
Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront
Knowing enough about the technology to work effectively with your technical team
Getting the data right: sourcing, collection, governance, security, and culture
Solving harder problems: exploring deep learning and other advanced techniques
Understanding today's machine learning software and hardware ecosystem
Evaluating potential projects, and addressing workforce concerns
Staffing your project, acquiring the right tools, and building a workable project plan
Interpreting results -- and building an organization that can increasingly learn from data
Using machine learning responsibly and ethically
Preparing for tomorrow's advances

The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.

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