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Machine Learning with Scikit-Learn and TensorFlow: Deep Learning with Python (Random Forests, Decision Trees, and Neural Networks)

Machine Learning with Scikit-Learn and TensorFlow: Deep Learning with Python (Random Forests, Decision Trees, and Neural Networks)

Machine Learning with Scikit-Learn and TensorFlow: Deep Learning with Python
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Machine Learning with Scikit-Learn and TensorFlow: Deep Learning with Python (Random Forests, Decision Trees, and Neural Networks) Paperback - 2019

by Emery H Maxwell

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  • Title Machine Learning with Scikit-Learn and TensorFlow: Deep Learning with Python (Random Forests, Decision Trees, and Neural Networks)
  • Author Emery H Maxwell
  • Binding Paperback
  • Condition New
  • Pages 54
  • Volumes 1
  • Language ENG
  • Publisher Independently Published
  • Publication date 2019-03-29
  • Bookseller's Inventory # 36770489
  • ISBN 9781092130776 / 1092130772
  • Weight 0.2 lbs (0.09 kg)
  • Dimensions 9 x 6 x 0.13 in (22.86 x 15.24 x 0.33 cm)
  • Category Computers - General Information
  • Quantity available 5

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Reader reviews for Machine Learning with Scikit-Learn and TensorFlow: Deep Learning with Python (Random Forests, Decision Trees, and Neural Networks)

From the publisher

It appears that the development of artificial intelligence is expanding. Certain tools are working behind the scenes of everyday life as prediction models by allowing computers to learn and act without human intervention.The result so far has been self-driving vehicles, improved internet browsing, and more.Even if you are not a programmer or data scientist, it can still be interesting to discover how machine learning works.This book is intended to guide you through the fundamentals of machine learning through Python, Scikit-Learn, and TensorFlow.It will cover: - An overview of Python, neural networks, Scikit-Learn, TensorFlow, random forests, decision trees, machine learning, and deep learning- How to get started with Python- How to run a line of code- How to get started with Scikit-Learn- How to work with data- How to use TensorFlow- How to use datasets- Computational graphs- How search algorithms work- How clustering algorithms work- . . . and more
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