Name: Deep Learning
Brand: The MIT Press
SKU: 153KM8MCHVMW
Price: 51.48 CAD
Availability: InStock
Rating: 4.7 (11 reviews)

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Deep Learning

<div><ul><li><span class="a-text-bold" style="color: rgb(15, 17, 17); font-family: &quot;Amazon Ember&quot;, Arial, sans-serif; font-size: 14px; font-weight: 700 !important;"><span style="font-family: &quot;Amazon Ember&quot;, Arial, sans-serif; font-weight: 400;">The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning.&nbsp;</span></span></li><li><span class="a-text-bold" style="color: rgb(15, 17, 17); font-family: &quot;Amazon Ember&quot;, Arial, sans-serif; font-size: 14px; font-weight: 700 !important;"><span style="font-family: &quot;Amazon Ember&quot;, Arial, sans-serif; font-weight: 400;">It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.&nbsp;</span></span></li><li><span class="a-text-bold" style="color: rgb(15, 17, 17); font-family: &quot;Amazon Ember&quot;, Arial, sans-serif; font-size: 14px; font-weight: 700 !important;"><span style="font-family: &quot;Amazon Ember&quot;, Arial, sans-serif; font-weight: 400;">Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.</span></span></li><li><span class="a-text-bold" style="color: rgb(15, 17, 17); font-family: &quot;Amazon Ember&quot;, Arial, sans-serif; font-size: 14px; font-weight: 700 !important;"><br></span></li><li><span class="a-text-bold" style="color: rgb(15, 17, 17); font-family: &quot;Amazon Ember&quot;, Arial, sans-serif; font-size: 14px; font-weight: 700 !important;">An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.</span></li><li>“Written by three experts in the field,&nbsp;<span class="a-text-italic" style="font-style: italic !important;">Deep Learning</span>&nbsp;is the only comprehensive book on the subject.”</li><li><span class="a-text-bold" style="font-weight: 700 !important;">—Elon Musk</span>, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX</li><li><span class="a-text-italic" style="font-family: &quot;Amazon Ember&quot;, Arial, sans-serif; font-style: italic !important;">Deep Learning</span><span style="font-family: &quot;Amazon Ember&quot;, Arial, sans-serif;">&nbsp;can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.</span></li></ul></div>

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[This review was collected as part of a promotion.] Good quality book in terms of print and paper quality.

Nice product

walmart.com

highly recommend

Great book. Easy to understand and thorough.

Concise

[This review was collected as part of a promotion.]

[This review was collected as part of a promotion.] This is a classic textbook for deep learning, comes with well-explained content. I would definitely recommend to read.

classic textbook, bit pricy.

[This review was collected as part of a promotion.] Printing is okay but binding isn't that great. But it's okay.

Binding isn't just okay.

The book is great. I like explanation. The quality of the book is a bit below par. The hard is a bit bent

Deep Learning book by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, published by The MIT Press. The cover features an artistic depiction of a landscape with trees, flowers, and abstract elements, blending natural and surreal imagery. Ideal for readers interested in machine learning, AI, and deep learning techniques.

Deep Learning

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