Introduction to Deep Learning

Machine Learning is Different
- h(x)
- questions machine learning can answer
- process
Building these things
- features to vectors
- mathematical representation
  - model
  - cost/reward function
- optimizing the things
  - gradients
Recognizing digits
- Graph
  - IN: Constants, Placeholders, Variables
  - OUT: Session params
- Run
linear model
- model + cost function
- tensorflow example
multi-layer linear model (MLP)
- model + cost function
- tensorflow example
better architecture
- convolutional neural network
- tensorflow example

Samples