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1
Introduction
2
Cross entropy loss
3
Data set
4
Tensorflow
5
Sample operation
6
Placeholders
7
Observations
8
Lowlevel Tensorflow
9
Training
10
Visualization
11
Examples
12
Pancake flipping robot
13
Skeleton walking robot
14
Alphago
15
Neural network architectures
16
Questions
Description:
Explore the cutting-edge world of machine learning and deep neural networks in this 37-minute Devoxx conference talk. Dive into the latest advancements in image recognition, natural language processing, and reinforcement learning. Learn how to apply these groundbreaking technologies to solve previously "impossible" problems without needing a PhD. Gain insights into neural network architectures, engineering best practices, and practical tips for implementing deep learning in your projects. Follow along as the speaker demonstrates real-world applications, including a pancake-flipping robot, a skeleton walking robot, and AlphaGo. Discover the power of TensorFlow, cross-entropy loss, and data visualization techniques. Whether you're a seasoned developer or new to machine learning, acquire the knowledge to leverage these transformative technologies in your work.

Tensorflow and Deep Reinforcement Learning, Without a PhD

Devoxx
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