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

By: Material type: TextTextLanguage: Bengali Publication details: New Delhi : SPD, 2017.Description: xx, 545 p. : ill. 24 cmISBN:
  • 9781491962268
  • 1491962267
  • 9781491962244
  • 1491962240
  • 9789352135219
Subject(s): Genre/Form: DDC classification:
  • 006.31 23 GEH 2017
Online resources:
Contents:
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 -- Neural networks and deep learning. Up and running with TensorFlow ; Introduction to artificial neural networks ; Training deep neural nets ; Distributing TensorFlow across devices and servers ; Convolutional neural networks ; Recurrent neural networks ; Autoencoders ; Reinforcement learning -- Exercise solutions -- Machine learning project checklist -- SVM dual problem -- Autodiff -- Other popular ANN architectures.
Summary: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
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Holdings
Item type Current library Call number Status Date due Barcode
Books Books Eastern University Library General Stacks 006.31 GEH 2017 (Browse shelf(Opens below)) Not For Loan 16367
Books Books Eastern University Library General Stacks 006.31 GEH 2017 (Browse shelf(Opens below)) Available 16368
Books Books Eastern University Library General Stacks 006.31 GEH 2017 (Browse shelf(Opens below)) Available 16369
Books Books Eastern University Library General Stacks 006.31 GEH 2017 (Browse shelf(Opens below)) Available 16370
Books Books Eastern University Library General Stacks 006.31 GEH 2017 (Browse shelf(Opens below)) Available 16371

Includes index.

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 -- Neural networks and deep learning. Up and running with TensorFlow ; Introduction to artificial neural networks ; Training deep neural nets ; Distributing TensorFlow across devices and servers ; Convolutional neural networks ; Recurrent neural networks ; Autoencoders ; Reinforcement learning -- Exercise solutions -- Machine learning project checklist -- SVM dual problem -- Autodiff -- Other popular ANN architectures.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.

Kamrul Islam

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Last Updated on 16 October 2024
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