Banner

Python machine learning : machine learning and deep learning with Python, scikit-learn, and TensorFlow 2 / Sebastian Raschka, Vahid Mirjalili.

By: Raschka, Sebastian [author.]
Contributor(s): Mirjalili, Mahid [author.]
Material type: TextTextLanguage: English Summary language: English Series: Expert insightPublisher: Birmingham, UK : Packt Publishing, 2019Edition: Third editionDescription: xxi, 741 pages : illustrations (black and white) ; 24 cmContent type: text | still image Media type: computer Carrier type: online resourceSubject(s): Machine learning | Python (Computer program language) | Informatics and Computer Science March2020Genre/Form: -- Reading book Additional physical formats: Print version :: No titleDDC classification: 005.133
Contents:
Table of ContentsGiving Computers the Ability to Learn from DataTraining Simple ML Algorithms for ClassificationML Classifiers Using scikit-learnBuilding Good Training Datasets - Data PreprocessingCompressing Data via Dimensionality ReductionBest Practices for Model Evaluation and Hyperparameter TuningCombining Different Models for Ensemble LearningApplying ML to Sentiment AnalysisEmbedding a ML Model into a Web ApplicationPredicting Continuous Target Variables with Regression AnalysisWorking with Unlabeled Data - Clustering AnalysisImplementing Multilayer Artificial Neural NetworksParallelizing Neural Network Training with TensorFlowTensorFlow MechanicsClassifying Images with Deep Convolutional Neural NetworksModeling Sequential Data Using Recurrent Neural NetworksGANs for Synthesizing New DataRL for Decision Making in Complex Environments.
Summary: Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. This new third edition is updated for TensorFlow 2 and the latest additions to
Tags from this library: No tags from this library for this title. Log in to add tags.
    Average rating: 0.0 (0 votes)
Item type Current location Collection Call number Status Date due Barcode Item holds
Book - Borrowing Book - Borrowing Central Library
Lower Floor
Baccah 005.133 RAS (Browse shelf) Available 000049059
Total holds: 0

Includes bibliographical references and index.

Table of ContentsGiving Computers the Ability to Learn from DataTraining Simple ML Algorithms for ClassificationML Classifiers Using scikit-learnBuilding Good Training Datasets - Data PreprocessingCompressing Data via Dimensionality ReductionBest Practices for Model Evaluation and Hyperparameter TuningCombining Different Models for Ensemble LearningApplying ML to Sentiment AnalysisEmbedding a ML Model into a Web ApplicationPredicting Continuous Target Variables with Regression AnalysisWorking with Unlabeled Data - Clustering AnalysisImplementing Multilayer Artificial Neural NetworksParallelizing Neural Network Training with TensorFlowTensorFlow MechanicsClassifying Images with Deep Convolutional Neural NetworksModeling Sequential Data Using Recurrent Neural NetworksGANs for Synthesizing New DataRL for Decision Making in Complex Environments.

Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. This new third edition is updated for TensorFlow 2 and the latest additions to

In English; summary in English.

Description based on CIP data; resource not viewed.

There are no comments for this item.

to post a comment.