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Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow : concepts, tools, and techniques to build intelligent systems / Aurélien Géron.

By: Material type: TextTextLanguage: English Publisher: Sebastopol : O'Reilly Media, 2022Copyright date: ©2023Edition: Third editionDescription: 834 sidor illustrationer 23 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781098125974
Subject(s): DDC classification:
  • 006.31 23/swe
Online resources:
Contents:
Part I, The fundamentals of machine learning. The machine learning landscape ; End-to-end machine learning project ; Classification ; Training models ; Support vector machines ; Decision trees ; Ensemble learning and random forests ; Dimensionality reduction ; Unsupervised learning techniques -- Part II, Neural networks and deep learning. Introduction to artificial neural networks with Keras ; Training deep neural networks ; Custom models and training with TensorFlow ; Loading and preprocessing data with TensorFlow ; Deep computer vision using convolutional neural networks ; Processing sequences using RNNs and CNNs ; Natural language processing with RNNs and attention ; Autoencoders, GAN, and diffusion models ; Reinforcement learning ; Training and deploying TensorFlow models at scale ; Machine learning project checklist ; Autodiff ; Special data structures ; TensorFlow graphs.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Course book reference Högskolan Väst Våning 2 006.31 Géron Läses i biblioteket - Library use only 6004300073555
Course book Högskolan Väst Våning 2 Våning 2 006.31 Géron Checked out 2023-09-27 6004300073556
Total holds: 0

Part I, The fundamentals of machine learning. The machine learning landscape ; End-to-end machine learning project ; Classification ; Training models ; Support vector machines ; Decision trees ; Ensemble learning and random forests ; Dimensionality reduction ; Unsupervised learning techniques -- Part II, Neural networks and deep learning. Introduction to artificial neural networks with Keras ; Training deep neural networks ; Custom models and training with TensorFlow ; Loading and preprocessing data with TensorFlow ; Deep computer vision using convolutional neural networks ; Processing sequences using RNNs and CNNs ; Natural language processing with RNNs and attention ; Autoencoders, GAN, and diffusion models ; Reinforcement learning ; Training and deploying TensorFlow models at scale ; Machine learning project checklist ; Autodiff ; Special data structures ; TensorFlow graphs.

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