Refresh Your Home For Fall
To see product details, add this item to your cart. You can always remove it later.
Shipper / Seller
Amazon.com
Amazon.com
Shipper / Seller
Amazon.com
Returns
30-day refund / replacement
30-day refund / replacement
This item can be returned in its original condition for a full refund or replacement within 30 days of receipt.
Read full return policy
Payment
Secure transaction
Your transaction is secure
We work hard to protect your security and privacy. Our payment security system encrypts your information during transmission. We don’t share your credit card details with third-party sellers, and we don’t sell your information to others. Learn more
Gift options
Available at checkout
Available at checkout This item is a gift. Change
At checkout, you can add a custom message, a gift receipt for easy returns and have the item gift-wrapped
Added to

Sorry, there was a problem.

There was an error retrieving your Wish Lists. Please try again.

Sorry, there was a problem.

List unavailable.
Kindle app logo image

Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet, or computer - no Kindle device required.

Read instantly on your browser with Kindle for Web.

Using your mobile phone camera - scan the code below and download the Kindle app.

QR code to download the Kindle App

  • Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

Follow the authors

Get new release updates & improved recommendations
Joe Papa
Follow
Nikhil Buduma
Follow
Something went wrong. Please try your request again later.

Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

by Nithin Buduma (Author), Nikhil Buduma (Author), Joe Papa (Author) Format: Paperback
4.8 out of 5 stars (18)

Purchase options and add-ons

We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics.

The updated second edition of this book describes the intuition behind these innovations without jargon or complexity. Python-proficient programmers, software engineering professionals, and computer science majors will be able to reimplement these breakthroughs on their own and reason about them with a level of sophistication that rivals some of the best developers in the field.

  • Learn the mathematics behind machine learning jargon
  • Examine the foundations of machine learning and neural networks
  • Manage problems that arise as you begin to make networks deeper
  • Build neural networks that analyze complex images
  • Perform effective dimensionality reduction using autoencoders
  • Dive deep into sequence analysis to examine language
  • Explore methods in interpreting complex machine learning models
  • Gain theoretical and practical knowledge on generative modeling
  • Understand the fundamentals of reinforcement learning

Read more
Previous slide of product details
  1. ISBN-10
    149208218X
  2. ISBN-13
    978-1492082187
  3. Edition
    2nd
  4. Publisher
    O'Reilly Media
  5. Publication date
    June 21, 2022
  6. Language
    English
  7. Dimensions
    7 x 0.75 x 9.25 inches
  8. Print length
    387 pages
Next slide of product details

Frequently bought together

This item: Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
$50.99
Get it as soon as Saturday, Sep 19
Only 8 left in stock (more on the way).
Ships from and sold by Amazon.com.
+
AI Engineering: Building Applications with Foundation Models
$52.40
Get it as soon as Saturday, Sep 19
In Stock
Ships from and sold by Amazon.com.
+
Hands-On Large Language Models: Language Understanding and Generation
$37.68
Get it as soon as Saturday, Sep 19
In Stock
Ships from and sold by Amazon.com.
Total price: $00
To see our price, add these items to your cart.
Details
Added to Cart
Some of these items ship sooner than the others.
Show details Hide details
Choose items to buy together.

Customers also bought or read

Page 1 of 1Start over
Previous page
  4. Book cover Natural Language Processing with Transformers, Revised Edition
    Natural Language Processing with Transformers, Revised Edition
    Paperback
    $41.60
    FREE delivery Sat, Sep 19
  9. Book cover Deep Learning (Adaptive Computation and Machine Learning series)
    Deep Learning (Adaptive Computation and Machine Learning series)
    Hardcover
    $51.51
    FREE delivery Sep 20 - 24
  15. Book cover Deep Learning: Foundations and Concepts
    Deep Learning: Foundations and Concepts
    Hardcover
    $50.43
    FREE delivery Sep 23 - 25
  17. Book cover Learning Python: Powerful Object-Oriented Programming
    Learning Python: Powerful Object-Oriented Programming
    Paperback
    $53.66
    FREE delivery Sat, Sep 19
  20. Book cover Fundamentals of Data Engineering: Plan and Build Robust Data Systems
    Fundamentals of Data Engineering: Plan and Build Robust Data Systems
    Paperback
    $40.00
    FREE delivery Sep 27 - Oct 14
  21. Book cover Why Machines Learn: The Elegant Math Behind Modern AI
    Why Machines Learn: The Elegant Math Behind Modern AI
    Hardcover
    $18.13
    Delivery Sat, Sep 19
  24. Book cover Mathematics for Machine Learning
    Mathematics for Machine Learning
    Paperback
    $51.44
    FREE delivery Mon, Sep 21
  26. Book cover Understanding Deep Learning
    Understanding Deep Learning
    Hardcover
    $96.30
    FREE delivery Mon, Sep 21
  28. Book cover Hands-On Generative AI with Transformers and Diffusion Models
    Hands-On Generative AI with Transformers and Diffusion Models
    Paperback
    $45.20
    FREE delivery Sat, Sep 19
  30. Book cover Dive into Deep Learning
    Dive into Deep Learning
    Paperback
    $29.99
    Delivery Sat, Sep 19
Next page
Loading...

From the brand

  2. Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build...
    AI Engineering: Building Applications with Foundation Models
    An Illustrated Guide to AI Agents: Concepts and Code for Building Agents with LLMs, Tools, and Me...
    AI Agents: The Definitive Guide: Design, Deployment, and Evaluation for Production

    Machine Learning, AI & more

    Visit the Store

  3. Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Build...
    Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
    AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence
    Building Machine Learning Systems with a Feature Store: Batch, Real-Time, and LLM Systems

    Machine Learning

    Visit the Store

  4. AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, ...
    Generative AI Design Patterns: Solutions to Common Challenges When Building GenAI Agents and Appl...
    Designing AI Interfaces: Design Principles for Creative and Autonomous AI
    Building AI-Powered Products: The Essential Guide to AI and GenAI Product Management

    Artificial Intelligence

    Visit the Store

  5. Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
    Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
    Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play
    Deep Learning from Scratch: Building with Python from First Principles

    Deep Learning

    Visit the Store

  6. Practical Natural Language Processing: A Comprehensive Guide to Building Real-World NLP Systems
    Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications
    Designing Large Language Model Applications: A Holistic Approach to LLMs
    Learning LangChain: Building AI and LLM Applications with LangChain and LangGraph

    Language Processing (NLP, LLM)

    Visit the Store

  7. Sharing the knowledge of experts

    O'Reilly's mission is to change the world by sharing the knowledge of innovators. For over 40 years, we've inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.

    Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.

From the Publisher

Fundamentals of Deep Learning

From the Preface

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field. Large companies such as Google, Microsoft, and Facebook have taken notice and are actively growing in-house deep learning teams. For the rest of us, deep learning is still a pretty complex and difficult subject to grasp. Research papers are filled to the brim with jargon, and scattered online tutorials do little to help build a strong intuition for why and how deep learning practitioners approach problems. Our goal is to bridge this gap.

In this second edition, we provide more rigorous background sections in mathematics with the aim of better equipping you for the material in the rest of the book. In addition, we have updated chapters in sequence analysis, computer vision, and reinforcement learning with deep dives into the latest advancements in the fields. And finally, we have added new chapters in the fields of generative modeling and interpretability to provide you with a broader view of the field of deep learning. We hope that these updates inspire you to practice deep learning on their own and apply their learnings to solve meaningful problems in the real world.

Prerequisites and Objectives

This book is aimed at an audience with a basic operating understanding of calculus and Python programming. In this latest edition, we provide extensive mathematical background chapters, specifically in linear algebra and probability, to prepare you for the material that lies ahead.

By the end of the book, we hope you will be left with an intuition for how to approach problems using deep learning, the historical context for modern deep learning approaches, and a familiarity with implementing deep learning algorithms using the PyTorch open source library.

How Is This Book Organized?

The first chapters of this book are dedicated to developing mathematical maturity via deep dives into linear algebra and probability, which are deeply embedded in the field of deep learning. The next several chapters discuss the structure of feed-forward neural networks, how to implement them in code, and how to train and evaluate them on real-world datasets. The rest of the book is dedicated to specific applications of deep learning and understanding the intuition behind the specialized learning techniques and neural network architectures developed for those applications. Although we cover advanced research in these latter sections, we hope to provide a breakdown of these techniques that is derived from first principles and digestible.

Editorial Reviews

About the Author

Nithin Buduma is one of the first machine learning engineers at XY.ai, a start-up based out of Harvard and Stanford working to help healthcare companies leverage their massive datasets.

Nikhil Buduma is the cofounder and chief scientist of Remedy, a San Francisco-based company that is building a new system for data-driven primary healthcare. At the age of 16, he managed a drug discovery laboratory at San Jose State University and developed novel low-cost screening methodologies for resource-constrained communities. By the age of 19, he was a two-time gold medalist at the International Biology Olympiad. He later attended MIT, where he focused on developing large-scale data systems to impact healthcare delivery, mental health, and medical research. At MIT, he cofounded Lean On Me, a national nonprofit organization that provides an anonymous text hotline to enable effective peer support on college campus and leverages data to effect positive mental health and wellness outcomes. Today, Nikhil spends his free time investing in hard technology and data companies through his venture fund, Q Venture Partners, and managing a data analytics team for the Milwaukee Brewers baseball team.

Joe Papa has over 25 years experience in research & development and is the founder of INSPIRD.ai. He holds an MSEE and has led AI Research teams with PyTorch at Booz Allen and Perspecta Labs. Joe has mentored hundreds of Data Scientists and has taught 6,000+ students across the world on Udemy.

Product details

  • Publisher ‏ : ‎ O'Reilly Media
  • Publication date ‏ : ‎ June 21, 2022
  • Edition ‏ : ‎ 2nd
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 387 pages
  • ISBN-10 ‏ : ‎ 149208218X
  • ISBN-13 ‏ : ‎ 978-1492082187
  • Item Weight ‏ : ‎ 2.31 pounds
  • Dimensions ‏ : ‎ 7 x 0.75 x 9.25 inches
  • Best Sellers Rank: #1,233,491 in Books (See Top 100 in Books)
  • Customer Reviews:
    4.8 out of 5 stars (18)

About the authors

Follow authors to get new release updates, plus improved recommendations.
Previous page
  1. Joe Papa

    Joe Papa

    Brief content visible, double tap to read full content.
    Full content visible, double tap to read brief content.

    Joe Papa has over 25 years experience in research & development and is the founder of TeachMe.AI. He holds an MSEE and has led AI Research teams with PyTorch at Booz Allen and Perspecta Labs. Joe is currently Chief AI Engineer at Mobile Insights. He has mentored hundreds of Data Scientists and has taught 6,000+ students across the world with Udemy, Packt, and O'Reilly Media.

    See more on the author's page
  2. Nikhil Buduma

    Nikhil Buduma

    Brief content visible, double tap to read full content.
    Full content visible, double tap to read brief content.

    Discover more of the author’s books, see similar authors, read book recommendations and more.

    See more on the author's page
Next page

Related books

Page 1 of 1Start Over
Sponsored
Previous page
  1. Shop the Store on Amazon ›
    Understanding Deep Learning: Building Machine Learning Systems with PyTorch and TensorFlow: From Neural Networks (CNN, DNN, GNN, RNN, ANN, LSTM, GAN) to Natural Language Processing (NLP)
    Understanding Deep Learning: Building Machine Learning Systems with PyTorch and TensorFlow: From Neural Networks (CNN, DNN, GNN, RNN, ANN, LSTM, GAN) to Natural Language Processing (NLP)
    4.24.2 out of 5 stars118
    $54.34 List:$74.99
  2. Shop the Store on Amazon ›
    AI IN BUSINESS - AN EXECUTIVE GUIDE FOR BEGINNERS: Leverage Artificial Intelligence to Simplify Automation, Improve Data-Driven Decisions, Maximize ROI and Elevate Customer Experience
    AI IN BUSINESS - AN EXECUTIVE GUIDE FOR BEGINNERS: Leverage Artificial Intelligence to Simplify Automation, Improve Data-Driven Decisions, Maximize ROI and Elevate Customer Experience
    4.74.7 out of 5 stars32
    $16.99
  3. Shop the Store on Amazon ›
    Python Programming for Beginners: The Complete Python Coding Crash Course - Boost Your Growth with an Innovative Ultra-Fast Learning Framework and Exclusive Hands-On Interactive Exercises & Projects
    Python Programming for Beginners: The Complete Python Coding Crash Course - Boost Your Growth with an Innovative Ultra-Fast Learning Framework and Exclusive Hands-On Interactive Exercises & Projects
    4.54.5 out of 5 stars1,011
    $24.90
  4. Shop the Store on Amazon ›
    50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography
    50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography
    4.74.7 out of 5 stars118
    $33.77 List:$49.99
  5. Shop the Store on Amazon ›
    Step-by-Step Electrical Engineering: Learn and Apply Core Concepts Quickly. Build Your Knowledge with Practical Examples - No Background Required! Perfect for Aspiring Engineers and Enthusiasts!
    Step-by-Step Electrical Engineering: Learn and Apply Core Concepts Quickly. Build Your Knowledge with Practical Examples - No Background Required! Perfect for Aspiring Engineers and Enthusiasts!
    4.54.5 out of 5 stars367
    $19.99
Next page