Machine learning

Below is the list of contents related to machine learning. They are very useful for the “Data Science and Machine Learning for Geoscientists” module, can be applied for some MSci and UROP projects.

Table of contents:

• Chapter 0 – Introduction
• Chapter 1 – Neural Network
• Chapter 2 – Maximum Likelihood
• Chapter 3 – Cross Entropy
• Chapter 4 – Cost Function
• Chapter 5 – Gradient Descent 1
• Chapter 6 – Gradient Descent 2
• Chapter 7 – Real (Non-linear) Neural Network
• Chapter 8 – Feedforward
• Chapter 9 – Back Propagation
• Chapter 10 – General Back Propagation
• Chapter 11 – Underfitting and Overfitting
• Chapter 12 – Early-stopping, Dropout & Mini-batch
• Chapter 13 – Vanishing Gradient 1
• Chapter 14 – Vanishing Gradient 2
• Chapter 15 – Regularisation
• Chapter 16 – Other Activation Functions
• Chapter 17 – Local Minima Trap
• Chapter 18 – Softmax
• Chapter 19 – Hyper-Parameters
• Chapter 20 – Coding Example