Description

Book Synopsis

Chapter 1: Introduction to Machine Learning (ML) with the Raspberry Pi (RasPi).- Chapter 2: Exploration of ML data models: Part 1.- Chapter 3: Exploration of ML data models: Part 2.- Chapter 4: Preparation for Deep Learning.- Chapter 5: Practical deep learning ANN demonstrations.- Chapter 6: CNN demonstrations.- Chapter 7: Predictions using ANNs and CNNs.- Chapter 8: Predictions using CNNs and MLPs for medical research.- Chapter 9: Reinforcement Learning. 



Table of Contents

Chapter 1: Introduction to Machine Learning (ML) with the Raspberry Pi (RasPi)

Chapter 2: Exploration of ML data models: Part 1

Chapter 3: Exploration of ML data models: Part 2

Chapter 4: Preparation for Deep Learning

Chapter 5: Practical deep learning ANN demonstrations

Chapter 6: CNN demonstrations

Chapter 7: Predictions using ANNs and CNNs

Chapter 8: Predictions using CNNs and MLPs for medical research

Chapter 9: Reinforcement Learning.

Machine Learning with the Raspberry Pi

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    Order before 4pm tomorrow for delivery by Sat 20 Jun 2026.

    A Paperback by Donald J. Norris

    5 in stock


      View other formats and editions of Machine Learning with the Raspberry Pi by Donald J. Norris

      Publisher: Apress
      Publication Date: 11/30/2019 12:00:00 AM
      ISBN13: 9781484251737, 978-1484251737
      ISBN10: 1484251733
      Also in:
      Digital and IT general topics

      Description

      Book Synopsis

      Chapter 1: Introduction to Machine Learning (ML) with the Raspberry Pi (RasPi).- Chapter 2: Exploration of ML data models: Part 1.- Chapter 3: Exploration of ML data models: Part 2.- Chapter 4: Preparation for Deep Learning.- Chapter 5: Practical deep learning ANN demonstrations.- Chapter 6: CNN demonstrations.- Chapter 7: Predictions using ANNs and CNNs.- Chapter 8: Predictions using CNNs and MLPs for medical research.- Chapter 9: Reinforcement Learning. 



      Table of Contents

      Chapter 1: Introduction to Machine Learning (ML) with the Raspberry Pi (RasPi)

      Chapter 2: Exploration of ML data models: Part 1

      Chapter 3: Exploration of ML data models: Part 2

      Chapter 4: Preparation for Deep Learning

      Chapter 5: Practical deep learning ANN demonstrations

      Chapter 6: CNN demonstrations

      Chapter 7: Predictions using ANNs and CNNs

      Chapter 8: Predictions using CNNs and MLPs for medical research

      Chapter 9: Reinforcement Learning.

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