Fundamentals of deep learning :

By:

Buduma, Nikhil

Contributor(s):

Locascio, Nicholas

Material type: Text

TextPublication details: Mumbai : Shroff Publishers, 2017Edition: First editionDescription: xii, 283 pages : illustrations (some color)ISBN:

9781491925614
9789352135608

Subject(s):

DDC classification:

006.31 BUD

Contents:

The neural network -- Training feed-forward neural networks -- Implementing neural networks in TensorFlow -- Beyond gradient descent -- Convolutional neural networks -- Embedding and representation learning -- Models for sequence analysis -- Memory augmented neural networks -- Deep reinforcement learning.

Summary: In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. If you're familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started

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Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Lending Books	Main Library Stacks	REF	006.31 BUD (Browse shelf(Opens below))	Available		015589

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Previous	005.82 STA Cryptography and network security : principles and practice	006.3 ADV Advanced analytics with Spark : patterns for learning from data at scale	006.3 ZUR Introduction to artificial neural systems	006.31 BUD Fundamentals of deep learning :	006.31 GOL Genetic algorithms in search, optimization, and machine learning	006.31 KIR Thoughtful machine learning with Python : a test-driven approach	006.31 WIC R for data science : import, tidy, transform, visualize, and model data	Next

Originally published in Sebastopol, CA. by O'Reilly Media,

In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. If you're familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started

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