Listen free for 30 days

Listen with offer

Preview
  • Deep Learning

  • MIT Press Essential Knowledge Series
  • By: John D. Kelleher
  • Narrated by: Joel Richards
  • Length: 5 hrs and 49 mins
  • 4.3 out of 5 stars (12 ratings)

£0.00 for first 30 days

Pick 1 audiobook a month from our unmatched collection - including bestsellers and new releases.
Listen all you want to thousands of included audiobooks, Originals, celeb exclusives, and podcasts.
Access exclusive sales and deals.
£7.99/month after 30 days. Renews automatically. See here for eligibility.

Deep Learning

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

£7.99/month after 30 days. Renews automatically. See here for eligibility.

Buy Now for £12.99

Buy Now for £12.99

Pay using card ending in
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.

Summary

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
activate_Holiday_promo_in_buybox_DT_T2

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
Machine Learning 2020 cover art
Machine Learning 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

What listeners say about Deep Learning

Average customer ratings
Overall
  • 4 out of 5 stars
  • 5 Stars
    6
  • 4 Stars
    5
  • 3 Stars
    0
  • 2 Stars
    0
  • 1 Stars
    1
Performance
  • 4.5 out of 5 stars
  • 5 Stars
    6
  • 4 Stars
    5
  • 3 Stars
    0
  • 2 Stars
    0
  • 1 Stars
    0
Story
  • 5 out of 5 stars
  • 5 Stars
    8
  • 4 Stars
    1
  • 3 Stars
    0
  • 2 Stars
    0
  • 1 Stars
    0

Reviews - Please select the tabs below to change the source of reviews.

Sort by:
Filter by:
  • Overall
    4 out of 5 stars
  • Performance
    5 out of 5 stars

Great book but needs a pdf for formulas

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.

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

You voted on this review!

You reported this review!

  • Overall
    4 out of 5 stars
  • Performance
    5 out of 5 stars
  • Story
    5 out of 5 stars

Comprehensive but not overly detailed

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.

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

You voted on this review!

You reported this review!

  • Overall
    5 out of 5 stars
  • Performance
    4 out of 5 stars
  • Story
    5 out of 5 stars

Imagination

the book is well written with explanation that allows you to imagine the workings of deep learning models.

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

You voted on this review!

You reported this review!

1 person found this helpful

  • Overall
    4 out of 5 stars
  • Performance
    5 out of 5 stars
  • Story
    5 out of 5 stars

Excellent content but needs a pdf

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.

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

You voted on this review!

You reported this review!

3 people found this helpful