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Human-In-The-Loop Machine Learning

by Robert Munro
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Current price ₹5,026.00
Original price ₹5,628.00
Original price ₹5,628.00
Original price ₹5,628.00
(-11%)
₹5,026.00
Current price ₹5,026.00

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Book cover type: Paperback
  • ISBN13: 9781617296741
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Manning Publications
  • Publisher Imprint: Manning Publications
  • Publication Date:
  • Pages: 325
  • Original Price: USD 59.99
  • Language: English
  • Edition: N/A
  • Item Weight: 726 grams
  • BISAC Subject(s): Data Science / Machine Learning, Human-Computer Interaction (HCI), and Data Science / Neural Networks

From the Back Cover

Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms.

Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process.

Key Features

- Active Learning to sample the right data for humans to annotate

- Annotation strategies to provide the optimal interface for human feedback

- Supervised machine learning design and query strategies to support Human-in-the-Loop systems

- Advanced Adaptive Learning approaches

- Real-world use cases from well-known data scientists

For software developers and data scientists with some basic Machine

Learning experience.

About the technology

"Human-in-the-Loop machine learning" refers to the need for human interaction with machine learning systems to improve human performance, machine performance, or both. Ongoing human involvement with the right interfaces expedites the efficient labeling of tricky or novel data that a machine can't process, reducing the potential for data-related errors.

Robert (Munro) Monarch is a data scientist and engineer who has built machine learning data for companies such as Apple, Amazon, Google, and IBM. He holds a PhD from Stanford.

Robert holds a PhD from Stanford focused on Human-in-the-Loop machine learning for healthcare and disaster response, and is a disaster response professional in addition to being a machine learning professional. A worked example throughout this text is classifying disaster-related messages from real disasters that Robert has helped respond to in the past.

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