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Deep Learning with Python
- Narrated by: Mark Thomas
- Length: 9 hrs and 55 mins
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Publisher's summary
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this audiobook builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.
- Deep learning from first principles
- Setting up your own deep-learning environment
- Image-classification models
- Deep learning for text and sequences
- Neural style transfer, text generation, and image generation
Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning - a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications.
François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
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Technical knowledge alone isn't enough - increase your software development income by leveling up your soft skills Early in his software developer career, John Sonmez discovered that technical knowledge alone isn't enough to break through to the next income level - developers need "soft skills" like the ability to learn new technologies just in time, communicate clearly with management and consulting clients, negotiate a fair hourly rate, and unite teammates and coworkers in working toward a common goal.
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The Complete Bro-grammer's Career Guide
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Artificial Intelligence helps choose what books you buy, what movies you see, and even who you date. It puts the "smart" in your smartphone and soon it will drive your car. It makes most of the trades on Wall Street, and controls vital energy, water, and transportation infrastructure. But Artificial Intelligence can also threaten our existence. In as little as a decade, AI could match and then surpass human intelligence. Corporations and government agencies are pouring billions into achieving AI’s Holy Grail - human-level intelligence.
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Kind of chilling
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Everything is a computer. Ovens are computers that make things hot; refrigerators are computers that keep things cold. These computers - from home thermostats to chemical plants - are all online. All computers can be hacked. And Internet-connected computers are the most vulnerable. Forget data theft: Cutting-edge digital attackers can now crash your car, your pacemaker, and the nation’s power grid. In Click Here to Kill Everybody, renowned expert and best-selling author Bruce Schneier examines the hidden risks of this new reality.
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Same old Bruce
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Prediction Machines
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Artificial intelligence does the seemingly impossible - driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.
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Not sure what I was expecting, but underwhelmed
- By William J Brown on 09-27-18
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ready for interview
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What listeners say about Deep Learning with Python
Average customer ratingsReviews - Please select the tabs below to change the source of reviews.
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- Alexander K. Weber
- 09-30-19
Supplimentary to the written version
The audio book is great if you also have a written version of it. I listened to this during my commute and caught up with the code examples later when I was with my laptop. This was a great book and the audio book was a great suppliment.
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1 person found this helpful
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- Kevin P. Monaghan
- 07-07-19
Outstanding Book
Great book and very easy to listen to while driving! Follow this author at @fchollet on Twitter...
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- Bjørnar Dervo
- 02-21-20
ok for getting keywords
I halfway listened to this book to get the keywords of deep learning, and got that. However the book do a lot of referencing to tables, links and images which is difficult to follow when you dont have them in front of you.
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- Sooch San Souci
- 08-23-19
Excellent Text as a Serious Introduction
Deep Learning with Python provides the required vocabulary, examples and overview to begin to understand how Python, Keras and TensorFlow are being used today to build predictive neural nets. I'm looking forward to François's followup text written for advanced programmers. The code examples are not read by the narrator, therefore the printed text is recommended as a support. A powerful way to retain this information is to read, then listen, then re-read, then re-listen to each chapter, following common guidelines for optimizing the interval between each visit. https://ncase.me/remember/ Part 2 "The Science of Spaced Repetition".
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- Graham
- 10-30-18
Almost Perfect - Better when paired with the book
Having such a technical book read aloud is awesome. And as far as the coverage of the subject matter, this is also fantastic as many Amazon reviewers will attest to. The only problem with the Audible version is that it was never intended to be used in isolation. The PDF that accompanies the Audible version contains numbered figures as well as some unnumbered code snippets. The problem is that many (maybe half) of the code snippets are missing from the PDF. For example the narrator will read the line "Finally, this was the training loop:", then he will ignore the code snippet and seamlessly continue with the next paragraph. You may not realize he is referring to some code, and even if you did, you would not know which code snippet because they are all unnumbered or simply missing form the PDF altogether. This is why this audio book is really only useful when paired with the eBook or physical book.
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23 people found this helpful
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- Riccardo Esclapon
- 05-26-20
Great book, not the greatest voice recordings
The book is really well written and explained, but personally I found the voice to be monotone and a bit boring but I imagine that depends a lot on who's listening.
I also had other problems with the audio, including the fact that the narrator does not read which figure the text refers to, meaning he will just say "like this:" and not say which figure it is. This problem is compounded by the fact that the chapters in the PDF and the audiobook are offset from each other.
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- Ken
- 01-31-21
Very Good Book on the Topic
I'm sure it is challenging to write a book on this technical topic in the form of an audio book. The PDF file helped, but there were many times a url was referenced without speaking it or providing the url in the PDF file.
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- Amazon Customer
- 11-20-18
does not translate well to audiobook
it does a great job talking through complex material, but many concepts appear to be visual in nature. I believe this would be better ingested in a reading format.
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5 people found this helpful
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- Redneck
- 02-20-19
Skip the Audible, buy the book
This is a good introduction to the subject of deep learning, but the audible format just doesn't suit it. He is constantly making references to illustrations. There is a PDF to download which contains most but not all of the illustrations. Also, he often references "this URL" in the audible but never specifies what the URL is. The accompanying PDF does not contain those URL references, at all, anywhere. Also, images on the PDF are such that they do not align with page breaks when printing. Thus images are split in half, with the top of the image on the bottom of one page, and the bottom of the image on the top of the next page. Overall a disapointingly sloppy implementation.
Don't get me wrong, I think this is a really good book. It is only valuable as an audible if you own the physical book and want it read to you. I am probably going to try to return it as an audible and purchase the physical book instead.
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10 people found this helpful