Week 1 - Neural Networks, Deep Learning, and TensorFlow
- Eager Execution
- Linear Regression with TensorFlow
- Logistic Regression with TensorFlow
- Deep Neural Networks
Week 2 - Supervised Learning Models (CNNs)
- Convolutional Neural Networks (CNNs)
- CNNs for Classification
- CNNs Architecture
- CNN with TensorFlow
Week 3 - Supervised Learning Models (RNNs, LSTM Model, Language Modelling)
- Recurrent Neural Networks (RNNs)
- Long Short Term Memory (LSTM) Model
- Language Modelling
- Language Modelling with LSTM
Week 4 - Unsupervised Deap Learning Models (RBMs)
- Restricted Boltzmann Machines (RBMs)
week 5 - Unsupervised Deep Learning Models and scaling (Autoencoders)
- Autoencoders