Title: Advanced Deep Learning with Python: Design and implement advanced next-generation AI solutions using TensorFlow and PyTorch
Publisher: Packt Publishing
Publication Date: 2019
Language: English
ISBN 10: 178995617X
ISBN 13: 9781789956177
Binding: Soft cover
Condition: new

About this title

Synopsis

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystem

Key Features

Get to grips with building faster and more robust deep learning architectures
Investigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorch
Apply deep neural networks (DNNs) to computer vision problems, NLP, and GANs

Book Description

In order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models. In this book, you'll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application.

You'll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you'll focus on variational autoencoders and GANs. You'll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You'll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you'll use graph neural networks for processing structured data, along with covering meta-learning, which allows you to train neural networks with fewer training samples. Finally, you'll understand how to apply deep learning to autonomous vehicles.

By the end of this book, you'll have mastered key deep learning concepts and the different applications of deep learning models in the real world.

What you will learn

Cover advanced and state-of-the-art neural network architectures
Understand the theory and math behind neural networks
Train DNNs and apply them to modern deep learning problems
Use CNNs for object detection and image segmentation
Implement generative adversarial networks (GANs) and variational autoencoders to generate new images
Solve natural language processing (NLP) tasks, such as machine translation, using sequence-to-sequence models
Understand DL techniques, such as meta-learning and graph neural networks

Who this book is for

This book is for data scientists, deep learning engineers and researchers, and AI developers who want to further their knowledge of deep learning and build innovative and unique deep learning projects. Anyone looking to get to grips with advanced use cases and methodologies adopted in the deep learning domain using real-world examples will also find this book useful. Basic understanding of deep learning concepts and working knowledge of the Python programming language is assumed.

The Nuts and Bolts of Neural Networks
Understanding Convolutional Networks
Advanced Convolutional Networks
Object Detection and Image Segmentation
Generative Models
Language Modelling
Understanding Recurrent Networks
Sequence-to-Sequence Models and Attention
Emerging Neural Network Designs
Meta Learning
Deep Learning for Autonomous Vehicles

About the Author

Ivan Vasilev started working on the first open source Java deep learning library with GPU support in 2013. The library was acquired by a German company, where he continued to develop it. He has also worked as a machine learning engineer and researcher in the area of medical image classification and segmentation with deep neural networks. Since 2017, he has been focusing on financial machine learning. He is working on a Python-based platform that provides the infrastructure to rapidly experiment with different machine learning algorithms for algorithmic trading. Ivan holds an MSc degree in artificial intelligence from the University of Sofia, St. Kliment Ohridski.

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

Store Description

We are dedicated to providing customers with easy, flawless transactions and excellent books! We provide 100% customer satisfaction and are always here to answer any questions or concerns for our customers.

Visit Seller's Storefront

Seller's business information

Farm For Books Inc
1734 Bellaire Street, Denver, CO, 80220, U.S.A.

Sale & Shipping Terms

Terms of Sale

We ship from Colorado, U.S.A!

Right of cancellation

If you are a consumer you can cancel 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 CANCELLATION

Statutory Right to cancel

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

The cancellation 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 the last good or the last lot or piece.

To exercise the right to cancel, you must inform us, RushLtd, 6800 E 53rd Pl., 80022, Denver, Colorado, U.S.A., +1 (303)550-1251, of your decision to cancel this contract by a clear statement (e.g. a letter sent by post, fax or e-mail). You may use the attached model cancellation form, but it is not obligatory. You can also electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". If you use this option, we will communicate to you an acknowledgement of receipt of such a cancellation on a durable medium (e.g. by e-mail) without delay.

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

Effects of cancellation

If you cancel 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 cancel with 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 us or RushLtd, 6800 E 53rd Pl., 80022, Denver, Colorado, U.S.A., +1 (303)550-1251, without undue delay and in any event not later than 14 days from the day on which you communicate your cancellation 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 cancellation

The right of cancellation 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 cancel it once delivery had started.

Model withdrawal form

(complete and return this form only if you wish to withdraw from the contract)

To: (RushLtd, 6800 E 53rd Pl., 80022, Denver, Colorado, U.S.A., +1 (303)550-1251)

I/We (*) hereby give notice that I/We (*) withdraw from my/our (*) contract of sale of the following goods (*)/for the provision of the following goods (*)/for the provision of the following service (*),

Ordered on (*)/received on (*)

Name of consumer(s)

Address of consumer(s)

Signature of consumer(s) (only if this form is notified on paper)

Date

* Delete as appropriate.

Shipping Terms

Shipping rates within U.S.A.

Shipping rates within U.S.A.
Order quantity	7 to 12 business days	4 to 6 business days
First item	� 3.17	� 11.17

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.