## Coursera Specialisation (Andrew Ng)

- Using Python, NumPy, Tensorflow and Keras in Jupyter Notebooks
- The honour code does not permit making solutions public so I cannot share assignments on GitHub
- Course Notes

A series of 5 courses make up this specialisation

- Neural Networks & Deep Learning
- Introduction
- Basics
- Assignment: Logistic Regression with a Neural Network Mindset

- One hidden layer
- Assignment: Planar Data Classification with One Hidden Layer

- Deep Neural Networks
- Assignment: Building a Neural Network- Step by Step
- Assignment: Deep Neural Network for Image Classification

- Improving Deep Neural Networks: Hyperparameter Tuning, Regularisation & Optimisation
- Practical aspects
- Assignment: Initialisation
- Assignment: Regularisation
- Assignment: Gradient Checking

- Optimisation algorithms
- Assignment: Optimisation Methods

- Hyperparameter tuning, batch normalisation & programming frameworks
- Assignment: TensorFlow Tutorial

- Practical aspects
- Structuring Machine Learning Projects
- Best practice
- Differing distributions
- Bias / variance analysis
- Error analysis
- Transfer learning & multi-task learning
- End to end deep learning

- Convolutional Neural Networks
- Foundations
- Assignment: Building a Convolution Model- Step by Step
- Assignment: Convolution Model for Image Classification

- Deep convolutional model case studies
- Assignment: Keras Tutorial – Detecting Happy Faces
- Assignment: Residual Networks

- Object detection
- Assignment: Autonomous Driving – Car Detection

- Special applications: Face recognition & neural style transfer
- Assignment: Art Generation with Neural Style Transfer

- Foundations
- Sequence Models
- RNNs (LSTM models)
- Assignment: Building a Recurrent Neural Network – Step by Step
- Assignment: Character level language model – Inventing Dinosaur Names
- Assignment: Improvise a Jazz Solo with an LSTM Network

- Natural language processing & word embeddings
- Assignment: Operations on word vectors
- Assignment: Emojis from Word Vector Representations

- Sequence models & attention mechanism
- Assignment: Neural Machine Translation with Attention
- Assignment: Trigger Word Detection

- RNNs (LSTM models)