Fundamentals of deep learning: designing next generation machine intelligence algorithms
Publication details: Beijing: O'Reilly Media, 2022.Edition: 2ndDescription: xiii, 372p.: ill; pbk: 23cmISBN:- 9789355420121
- 006.31 BUD
Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode |
---|---|---|---|---|---|---|---|
Books | IIT Gandhinagar | General | 006.31 BUD (Browse shelf(Opens below)) | 1 | Checked out | 02/08/2024 | 033185 |
Includes bibliographical references and index.
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
https://www.oreilly.com/library/view/fundamentals-of-deep/9781492082170/
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