Unit 4 Sprint 3: Major Neural Network Architectures

This week we will review several popular feed-forward neural network architectures that are common in commercial applications.

Module 1: RNNs & LSTMs
- Objectives:
  1. Describe recurrent neural network architecture
    - Neural network architecture description provided
  2. Use an LSTM to generate text based on some input
    - Need to go back and review LSTM model for text generation
Module 2: CNNs
- Objectives:
  1. Describe convolutions and convolutions within neural networks
    - Need to read through more conv literature
  2. Apply pre-trained CNNs to object detection problems
    - CNNs applied to object detection poroblems, but what more can we do with this?
Module 3: Autoencoders
- Objectives:
  1. Describe the componenets of an autoencoder
    - need to complete all of these
  2. Train an autoencoder
  3. Apply an autoencoder to a basic information retreval problem
Module 4: Artificial General Intelligence & the Future
- Objectives:
  1. Describe the history of artificial intelligence research
  2. Know the important research achievements in AI
  3. Delineate the ethnical challenges faces AI