Title: Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks
Publisher: Packt Publishing
Publication Date: 2020
Language: English
ISBN 10: 1838647295
ISBN 13: 9781838647292
Binding: Soft cover
Condition: very_good

About this title

Synopsis

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures

Key Features

Understand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networks
Learn the mathematical concepts needed to understand how deep learning models function
Use deep learning for solving problems related to vision, image, text, and sequence applications

Book Description

Most programmers and data scientists struggle with mathematics, having either overlooked or forgotten core mathematical concepts. This book uses Python libraries to help you understand the math required to build deep learning (DL) models.

You'll begin by learning about core mathematical and modern computational techniques used to design and implement DL algorithms. This book will cover essential topics, such as linear algebra, eigenvalues and eigenvectors, the singular value decomposition concept, and gradient algorithms, to help you understand how to train deep neural networks. Later chapters focus on important neural networks, such as the linear neural network and multilayer perceptrons, with a primary focus on helping you learn how each model works. As you advance, you will delve into the math used for regularization, multi-layered DL, forward propagation, optimization, and backpropagation techniques to understand what it takes to build full-fledged DL models. Finally, you'll explore CNN, recurrent neural network (RNN), and GAN models and their application.

By the end of this book, you'll have built a strong foundation in neural networks and DL mathematical concepts, which will help you to confidently research and build custom models in DL.

What you will learn

Understand the key mathematical concepts for building neural network models
Discover core multivariable calculus concepts
Improve the performance of deep learning models using optimization techniques
Cover optimization algorithms, from basic stochastic gradient descent (SGD) to the advanced Adam optimizer
Understand computational graphs and their importance in DL
Explore the backpropagation algorithm to reduce output error
Cover DL algorithms such as convolutional neural networks (CNNs), sequence models, and generative adversarial networks (GANs)

Who this book is for

This book is for data scientists, machine learning developers, aspiring deep learning developers, or anyone who wants to understand the foundation of deep learning by learning the math behind it. Working knowledge of the Python programming language and machine learning basics is required.

Linear Algebra
Vector Calculus
Probability and Statistics
Optimization
Graph Theory
Linear Neural Networks
Feedforward Neural Networks
Regularization
Convolutional Neural Networks
Recurrent Neural Networks
Attention Mechanisms
Generative Models
Transfer and Meta Learning
Geometric Deep Learning

About the Author

Jay Dawani is a former professional swimmer turned mathematician and computer scientist. He is also a Forbes 30 Under 30 Fellow. At present, he is the Director of Artificial Intelligence at Geometric Energy Corporation (NATO CAGE) and the CEO of Lemurian Labs - a startup he founded that is developing the next generation of autonomy, intelligent process automation, and driver intelligence. Previously he has also been the technology and R&D advisor to Spacebit Capital. He has spent the last three years researching at the frontiers of AI with a focus on reinforcement learning, open-ended learning, deep learning, quantum machine learning, human-machine interaction, multi-agent and complex systems, and artificial general intelligence.

"About this title" may belong to another edition of this title.

Store Description

We are a local book store that specializes in used books. Our delivery is quick. Same day shipping most of the time and most books arrive within 5 days or ordering.

Visit Seller's Storefront

Seller's business information

Bay State Book Company LLC
473 saint paul st, suite 1 (Bay State Books), North Smithfield, RI, 02896, U.S.A.

Sale & Shipping Terms

Terms of Sale

Right of withdrawal

If you are a consumer you can withdraw from the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.

Information regarding the right of withdrawal

Statutory right to withdraw

You have the right to withdraw from this contract within 14 days without giving any reason.

The withdrawal period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the last good or the last lot or piece.

To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.

To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.

Effects of withdrawal

If you withdraw from this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).

We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.

We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to withdraw from this contract.

We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.

We may withhold reimbursement until we have received the goods back, or you have supplied evidence of having sent back the goods, whichever is the earliest.

You shall send back the goods or hand them over to Bay State Book Company, North Smithfield, Rhode Island, U.S.A., without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.

Exceptions to the right of withdrawal

The right of withdrawal does not apply to:

The delivery of newspapers, journals or magazines with the exception of subscription contracts; and
The supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not withdraw once delivery had started.

Shipping Terms

Shipping rates within U.S.A.

Shipping rates within U.S.A.
Order quantity	4 to 11 business days	4 to 10 business days
First item	� 0.00	� 4.44

Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.