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Python machine learning : machine learning and deep learning with python, scikit-learn, and tensorflow 2

By: Raschka, SebastianContributor(s): Mirjalili, VahidMaterial type: Text

TextPublication details: Birmingham : Packt Publishing, Limited, [2019] ©2019Edition: Third editionDescription: xxi, 741 pages : illustrationsISBN: 9781789955750Subject(s): PythonDDC classification: 005.133

Contents:

Giving computers the ability to learn from data -- Training simple machine learning algorithms for classification -- A tour of machine learning classifiers using scikit-learn -- Building good training sets-data preprocessing -- Compressing data via dimensionality reduction -- Learning best practices for model evaluation and hyperparmeter tuning -- Combining different models for ensemble learning -- Applying machine learning to sentiment analysis -- Embedding a machine learning model into a web application -- Predicting continuous target variables with regression analysis -- Working with unlabeled data-clustering analysis -- Implementing a multilayer artificial neural network from Scratch -- Parallelizing neural network training with TensorFlow -- Going deeper -- The mechanics of TensorFlow -- Classifying images with deep convolutional neural networks -- Modeling sequential data using recurrent neural networks -- Generative adversarial networks for synthesizing new data -- Reinforcement learning 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 ...

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Reference Books	Main Library Reference	Reference	005.133 RAS (Browse shelf(Opens below))	Available		016122

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Previous	005.133 PUG C language for programmers /	005.133 QUI Parallel programming in C with MPI and openMP /	005.133 RAS Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics	005.133 RAS Python machine learning : machine learning and deep learning with python, scikit-learn, and tensorflow 2	005.133 RAS Machine learning with PyTorch and Scikit-Learn : develop machine learning and deep learning models with Python	005.133 RAY Perl and XML	005.133 ROB Python Programming for Beginners: The Complete Guide to Mastering Python in 7 Days with Hands-On Exercises – Top Secret Coding Tips to Get an Unfair Advantage and Land Your Dream Job!	Next

Includes index
"Third edition includes TensorFlow 2, GANS, and reinforcement learning"

Giving computers the ability to learn from data --
Training simple machine learning algorithms for classification --
A tour of machine learning classifiers using scikit-learn --
Building good training sets-data preprocessing --
Compressing data via dimensionality reduction --
Learning best practices for model evaluation and hyperparmeter tuning --
Combining different models for ensemble learning --
Applying machine learning to sentiment analysis --
Embedding a machine learning model into a web application --
Predicting continuous target variables with regression analysis --
Working with unlabeled data-clustering analysis --
Implementing a multilayer artificial neural network from Scratch --
Parallelizing neural network training with TensorFlow --
Going deeper --
The mechanics of TensorFlow --
Classifying images with deep convolutional neural networks --
Modeling sequential data using recurrent neural networks --
Generative adversarial networks for synthesizing new data --
Reinforcement learning 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 ...

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