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1
Introduction
2
Hacking Machine Learning
3
Deep Learning
4
Deep Learning is Everywhere
5
Why Use Deep Learning
6
Neural Networks
7
Convolutional Networks
8
Layered Learning
9
Recurrent Neural Networks
10
Text Generation
11
Long Term Memory
12
Speech Recognition
13
Machine Learning
14
Attack Text Economy
15
Blind Spots
16
Three Steps
17
First Way
18
Transferability
19
Substitute Models
20
False Assumptions
21
Three Methods
22
Deep Boning
23
Deep Learning Privacy
24
Questions
Description:
Explore the vulnerabilities of deep learning systems in this comprehensive conference talk from GrrCon 2016. Delve into the world of hacking machine learning, focusing on deep learning techniques and their widespread applications. Understand neural networks, convolutional networks, and recurrent neural networks, along with their roles in text generation, speech recognition, and long-term memory. Discover the potential attack vectors in the text economy and learn about blind spots in machine learning models. Examine three key steps and methods for exploiting deep learning systems, including transferability and substitute models. Gain insights into false assumptions and privacy concerns surrounding deep learning technologies. Conclude with a Q&A session to address specific inquiries about machine duping and pwning deep learning systems.

Machine Duping - Pwning Deep Learning Systems

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