Demystifying Deep Learning: An Introduction to the Mathematics of Neural Networks - Image 1

£98.44

Wiley-IEEE Press Demystifying Deep Learning: An Introduction to the Mathematics of Neural Networks

Name: Demystifying Deep Learning: An Introduction to the Mathematics of Neural Networks
Brand: Wiley-IEEE Press
Price: 98.44 GBP
Availability: InStock

AI & Machine Learning

This is the usual price. Wait for it to drop, or tell us your number.

£98 today · usual range £0–£0 · best ever £79

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 386 days • 386 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 386 days • 5 price ranges

Days at Price

Current Price

Price Analysis

Most common range: £83-88 (173 days, 44.8%)

Price range: £79 - £100

Price levels: 5 price ranges over 386 days

Description

DEMYSTIFYING DEEP LEARNING Discover how to train Deep Learning models by learning how to build real Deep Learning software libraries and verification software! The study of Deep Learning and Artificial Neural Networks (ANN) is a significant subfield of artificial intelligence (AI) that can be found within numerous fields: medicine, law, financial services, and science, for example. Just as the robot revolution threatened blue-collar jobs in the 1970s, so now the AI revolution promises a new era of productivity for white collar jobs. Important tasks have begun being taken over by ANNs, from disease detection and prevention, to reading and supporting legal contracts, to understanding experimental data, model protein folding, and hurricane modeling. AI is everywhere―on the news, in think tanks, and occupies government policy makers all over the world ―and ANNs often provide the backbone for AI. Relying on an informal and succinct approach, Demystifying Deep Learning is a useful tool to learn the necessary steps to implement ANN algorithms by using both a software library applying neural network training and verification software. The volume offers explanations of how real ANNs work, and includes 6 practical examples that demonstrate in real code how to build ANNs and the datasets they need in their implementation, available in open-source to ensure practical usage. This approachable book follows ANN techniques that are used every day as they adapt to natural language processing, image recognition, problem solving, and generative applications. This volume is an important introduction to the field, equipping the reader for more advanced study. Demystifying Deep Learning readers will also find: A volume that emphasizes the importance of classification Discussion of why ANN libraries, such as Tensor Flow and Pytorch, are written in C++ rather than Python Each chapter concludes with a “Projects” page to promote students experimenting with real code A supporting library of software to accompany the book at https://github.com/nom-de-guerre/RANT An approachable explanation of how generative AI, such as generative adversarial networks (GAN), really work. An accessible motivation and elucidation of how transformers, the basis of large language models (LLM) such as ChatGPT, work. Demystifying Deep Learning is ideal for engineers and professionals that need to learn and understand ANNs in their work. It is also a helpful text for advanced undergraduates to get a solid grounding on the topic.

Key Features

Demystifying Deep Learning: An Introduction to the Mathematics of Neural Networks

ABIS_BOOK

Product Specifications

Brand: Wiley-IEEE Press
Format: hardcover
ASIN: 1394205600
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 22 November 2023
Listed Since: 11 May 2023

Barcode

No barcode data available

Wiley-IEEE Press Demystifying Deep Learning: An Introduction to the Mathematics of Neural Networks

This is the usual price. Wait for it to drop, or tell us your number.

Price History & Forecast

Price Distribution

Price Analysis

Description

Key Features

Product Specifications

Barcode

Similar Products You Might Like

Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow

Pro Deep Learning with TensorFlow 2.0: A Mathematical Approach to Advanced Artificial Intelligence in Python

Learn Generative AI with PyTorch

Deep Learning: A Visual Approach

Machine Learning: From the Classics to Deep Networks, Transformers, and Diffusion Models

Penguin Random House Deep Learning (Adaptive Computation and Machine Learning series)

Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence (Addison-Wesley Data & Analytics Series)

Applied Generative AI for Beginners: Practical Knowledge on Diffusion Models, ChatGPT, and Other LLMs

Introduction to Machine Learning with Applications in Information Security (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Introduction to Machine Learning with Applications in Information Security (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

The Handbook of Data Science and AI: Generate Value from Data with Machine Learning and Data Analytics

Hands-On Artificial Intelligence for Beginners: An introduction to AI concepts, algorithms, and their implementation

Neural Networks and Deep Learning: A Textbook

A Developer's Guide to Integrating Generative AI into Applications (Tech Today)

Master AI From Beginner To Business Leader.: Discover How To Streamline Your AI Journey, From Beginner Tools To Cutting Edge Business Applications ... (Artificial Intelligence For Everyone.)

Explainable AI with Python

Generative AI in Action

Neural Networks and Deep Learning: A Textbook

Building AI Agents with LLMs, RAG, and Knowledge Graphs: A practical guide to autonomous and modern AI agents

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

Mastering PyTorch: Build powerful neural network architectures using advanced PyTorch 1.x features

Generative Adversarial Learning: Architectures and Applications: 217 (Intelligent Systems Reference Library, 217)

Generative AI and LLMs: Natural Language Processing and Generative Adversarial Networks

Understanding Deep Learning: Building Machine Learning Systems with PyTorch and TensorFlow: From Neural Networks (CNN, DNN, GNN, RNN, ANN, LSTM, GAN) to Natural Language Processing (NLP)