Deep Learning cover art

Deep Learning

MIT Press Essential Knowledge Series

 Preview
LIMITED TIME OFFER

3 months free
Try for £0.00
£8.99/mo thereafter. Renews automatically. Terms apply. Offer ends 31 July 2025 at 23:59 GMT.
Pick 1 audiobook a month from our unmatched collection.
Listen all you want to thousands of included audiobooks, Originals, and podcasts.
Access exclusive sales and deals.
Premium Plus auto-renews for £8.99/mo after 3 months. Cancel monthly.

Deep Learning

By: John D. Kelleher
Narrated by: Joel Richards
Try for £0.00

£8.99/mo after 3 months. Offer ends 31 July 2025 23:59 GMT. Cancel monthly.

Buy Now for £12.99

Buy Now for £12.99

Confirm Purchase
Pay using card ending in
Switch payment method
By completing your purchase, you agree to Audible's Conditions of Use and authorise Audible to charge your designated card or any other card on file. Please see our Privacy Notice, Cookies Notice and Interest-based Ads Notice.
Cancel

About this listen

Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.

Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning-major trends, possible developments, and significant challenges.

©2019 Massachusetts Institute of Technology (P)2019 Gildan Media Computer Science Machine Theory & Artificial Intelligence Technology Machine Learning Data Science Artificial Intelligence Programming

Listeners also enjoyed...

 Data Science cover art
Your Starter Guide for Data Management, Model Training, Neural Networks, Machine Learning Algorithms cover art
Python Programming cover art
Storytelling with Data cover art
Models of the Mind cover art
Neural Networks for Beginners cover art
Machine Learning for Beginners cover art
Algorithms: The Complete Guide to the Computer Science & Artificial Intelligence Used to Solve Human Decisions, Advance Technology, Optimize Habits, Learn Faster & Your Improve Life (Two-Book Bundle) cover art
Python Machine Learning cover art
Power and Prediction cover art
Machine Learning and Artificial Intelligence, Two-Book Bundle cover art
Python: 2 Books in 1 cover art
Neural Networks: Step-by-Step cover art
Deep Learning: Step-by-Step | A Sensible Guide Presenting the Concepts of Deep Learning with Real-World Examples cover art
Machine Learning: Neural Networks - Understand How Neural Networks Work & Deep Learning - A Sensible Guide Presenting the Concepts cover art
Deep Medicine cover art
All stars
Most relevant  
The content of the book and performance of the reader was great but the book contains a lot of formulas and plots and therefore a pdf would be a great addition to make it a five star book.

Great book but needs a pdf for formulas

Something went wrong. Please try again in a few minutes.
The author clearly explains all the concepts and ideas in a way that is approachable to non-specialists.

There are elements that don’t work brilliantly in this format (ie equations) but this isn’t a criticism of the book per se.

Short, easy to follow and to the point—it is a job well done.

Comprehensive but not overly detailed

Something went wrong. Please try again in a few minutes.
the book is well written with explanation that allows you to imagine the workings of deep learning models.

Imagination

Something went wrong. Please try again in a few minutes.
Very well-written but not a natural fit for an audiobook. It's essentially a book heavily dependent on mathematical expressions and neural network diagrams. The narrator makes a valiant attempt to describe diagrams, math, etc in words but, in the end, I bought the Kindle version to check my understanding. I found it stimulating to try and follow the audio math but it took some heavy-duty concentration.
Overall, I'd describe it as both excellent and hard work. It would greatly benefit from a pdf for the diagrams and math expressions.

Excellent content but needs a pdf

Something went wrong. Please try again in a few minutes.