--- product_id: 49898008 title: "Penguin Random House Deep Learning (Adaptive Computation and Machine Learning series)" price: "€ 129.78" currency: EUR in_stock: true reviews_count: 13 url: https://www.desertcart.it/products/49898008-penguin-random-house-deep-learning-adaptive-computation-and-machine-learning store_origin: IT region: Italy --- # Industry & research techniques Comprehensive deep learning coverage Strong math & theory foundation Penguin Random House Deep Learning (Adaptive Computation and Machine Learning series) **Price:** € 129.78 **Availability:** ✅ In Stock ## Summary > 🤖 Unlock the AI edge with the ultimate deep learning bible! ## Quick Answers - **What is this?** Penguin Random House Deep Learning (Adaptive Computation and Machine Learning series) - **How much does it cost?** € 129.78 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.it](https://www.desertcart.it/products/49898008-penguin-random-house-deep-learning-adaptive-computation-and-machine-learning) ## Best For - Customers looking for quality international products ## Why This Product - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Key Features - • **Expert Authorship:** Written by three leading AI experts, endorsed by Elon Musk for its authoritative insights. - • **Master the Foundations:** Covers essential math—linear algebra, probability, and information theory to build your deep learning expertise. - • **Future-Proof Your Skills:** Includes research perspectives and advanced topics to keep you ahead in the evolving AI landscape. - • **Industry-Ready Techniques:** Learn practical methods like convolutional networks, sequence modeling, and optimization algorithms used by top tech companies. - • **Broad Application Spectrum:** Explore real-world uses from NLP and speech recognition to computer vision and bioinformatics. ## Overview Penguin Random House's Deep Learning (Adaptive Computation and Machine Learning series) is a hardcover, English-language textbook offering a comprehensive introduction to deep learning. It blends rigorous mathematical foundations with practical industry techniques and advanced research topics, making it ideal for students, engineers, and professionals aiming to master AI's cutting edge. ## Description 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. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk , cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. 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. 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. Deep Learning 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. Review: authoritative book - helpful for anymore who wants an introductory (and broad) background to the field Review: A good comprensive textbook - This is a good comprehensive textbook starting at the basics (math, statistics and fundaments) of Machine Learning and Deep Learning. It is well aligned with eg MOOC courses in Machine Learning should you want to deepen your understanding. However, there are of course newer books, but this is worth buying a reference and as said a comprehensive textbook. ## Features - Language Published: English - Binding: hardcover - It ensures you get the best usage for a longer period ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | 161,012 in Books ( See Top 100 in Books ) 174 in Computer Information Systems 854 in Computing & Internet Programming 9,119 in Science & Nature Education (Books) | | Customer Reviews | 4.5 out of 5 stars 2,345 Reviews | ## Images ![Penguin Random House Deep Learning (Adaptive Computation and Machine Learning series) - Image 1](https://m.media-amazon.com/images/I/A10G+oKN3LL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ authoritative book *by M***I on 3 August 2025* helpful for anymore who wants an introductory (and broad) background to the field ### ⭐⭐⭐⭐⭐ A good comprensive textbook *by C***R on 31 August 2020* This is a good comprehensive textbook starting at the basics (math, statistics and fundaments) of Machine Learning and Deep Learning. It is well aligned with eg MOOC courses in Machine Learning should you want to deepen your understanding. However, there are of course newer books, but this is worth buying a reference and as said a comprehensive textbook. ### ⭐⭐⭐⭐⭐ A beautiful text. *by Z***N on 21 April 2017* This book serves as an excellent reference book but also as a book to settle down and contextualise your knowledge. For example, I went to read up on contrastive divergence which is often bunched together with restricted boltzmann machines (naturally). The text on contrastive divergence was within a practically self-contained chapter on monte carlo sampling. It was beautiful. The authors also succeed in contextualising these topics against all the necessary central theory but also the state of the art. This book deserves a place in anyone's collection even if you feel you possess other works which may contain the same topics. ## Frequently Bought Together - Deep Learning (Adaptive Computation and Machine Learning series) - Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems - Artificial Intelligence: A Modern Approach, Global Edition --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.it/products/49898008-penguin-random-house-deep-learning-adaptive-computation-and-machine-learning](https://www.desertcart.it/products/49898008-penguin-random-house-deep-learning-adaptive-computation-and-machine-learning) --- *Product available on Desertcart Italy* *Store origin: IT* *Last updated: 2026-06-27*