2. Agenda
1. Introduction to Deep Learning
2. Training You Own Deep Learning Model
a. Introduction to Tensorflow
3. What’s deep learning
1. Deep learning is part of a broader family of machine learning methods based
on learning representations of data.
2. Deep learning can be applied to binary classification problem ( ),
multiclass classification problem ( ).
3. Can we make machine learn by itself?
https://en.wikipedia.org/wiki/Deep_learning#Definitions
35. Agenda
1. Introduction to Deep Learning
2. Training you own Deep Learning model
a. use Tensorflow
Most of slides are borrowed from Dr. Chung-Cheng Chiu deep learning talk
36.
37.
38. TensorFlow
Developed by Google Brain Team
Initial release: November 9, 2015
Used for both Google production and research.
Production: 50 different teams in dozens of commercial Google products, such as Google Voice, Gmail, Google
Photos, and Search, etc
Feature:
Python, C/C++ API
support multiple CPUs and GPUs
support mobile computing platforms, including Android and Apple's iOS
39. TensorFlow = Tensor + Flow
Tensor: n-dimensional arrays
Flow: A sequence of tensor operations
Deep Learning is suitable for TensorFlow, but TensorFlow can do more
58. Conclusion
Neural network, Deep learning
Create a framework to let machine learn by itself
Sometimes it is too complex to debug
TensorFlow tool
Try to train you own model.
Define input, out, and run/train it