Python machine learning

Python machine learning: machine learning and deep learning with Python, scikit-learn, and TensorFlow

by Raschka, Sebastian

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Title Statements

  • Full title :Python machine learning : machine learning and deep learning with Python, scikit-learn, and TensorFlow / Sebastian Raschka, Vahid Mirajalili.

Edition Statements

  • Publication Date:2018.
  • Edition:2nd ed

Publication Statements

  • Publisher(s):Packt Publishing
  • Place of Publication:Birmingham, UK
  • Language:eng
  • Publication Date:2018.

Notes

Reprint. Originally published: 2017.

Includes index.

The Physical Object

  • Description:xviii, 595 pages : : illustrations

Edition Identifiers

  • ISBN:9781787125933, 1787125939
  • oclc:on1085295595
  • LC Classification:QA76.73.P98

Table of Contents

1. Giving computers the ability to learn from data -- 2. Training simple machine learning algorithms for classification -- 3. A tour of machine learning classifiers using scikit-learn -- 4. Building good training sets-data preprocessing -- 5. Compressing data via dimensionality reduction -- 6. Learning best practices for model evaluation and hyperpaarmeter tuning -- 7.Combining different models for ensemble learning -- 8. Applying machine learning to sentiment analysis -- 9. embedding a machine learning model into a web application -- 10. Predicting continuous target variables with regression analysis -- 11. Working with unlabeled data-clustering analysis -- 12. Implementing a multilayer artificial neural network from Scratch -- 13. Parallelizing neural network training with TensorFlow -- 14. Going deeper -- The mechanics of TensorFlow -- 15. Classifying images with deep convolutional neural networks -- 16. Modeling sequential data using recurrent neural networks.

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Subjects

Machine learning Python (Computer program language)

Writers

Raschka, Sebastian Mirajalili, Vahid

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