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[center][b][color=#ff0000][u][color=#ff3333]Fundamentals of Deep Learning Designing Next-Generation Machine Intelligence Algorithms, 2nd Edition (True PDF)[/color][/u][/color][/b][/center]


[center][img]https://i120.fastpic.org/thumb/2022/0710/4f/_5444f87344d11f4c9a84981e70b9fe4f.jpeg[/img][/center]

[center][color=#ff0033]English | 2022 | ISBN: ‎ 149208218X | 390 pages | True PDF | 15.93 MB[/color][/center]


[quote]
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.

[list]
[*] 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
[/list]

[/quote]


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