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Welcome to the Earth Data Science and Machine Learning Course Series

Introduction

What is machine learning?
Machine Learning for Climate and Environmental Sustainability
Computing Environment for Class

Data Preprocessing and Feature Engineering

Data Exploration and Data Pre-Processing
Tutorial on Data Preprocessing (US Wildfires)
Assignment 1: Data Pre-Processing of Historical Tropical Cyclone Records

Introduction to Supervised Machine Learning

Supervised Machine Learning
Supervised Classification
Supervised Regression
Decision Trees and Random Forests
Tutorial on Random Forests (Wildfire cause prediction)
Assignment 2: Predicting Health Impacts from Air Quality Factors

Unsupervised Machine Learning

Unsupervised Machine Learning
Dimensionality Reduction
Clustering
Tutorial on Dimensionality Reduction
Assignment 3: Using Unsupervised Machine Learning to Discover Climate Zones

Introduction to Deep Learning

Introduction to Artificial Neural Networks
Artificial Neural Networks (ANN): a hands-on tutorial
Convolutional Neural Networks
Tutorial on Global Temperature Trends with Deep Learning
Recurrent Neural Networks and Time Series
Tutorial on Rainfall-Runoff Modeling with RNNs
Assignment 4: Flood Risk Prediction with Neural Network Regression

Advanced Topics

Generative Models and Uncertainty
GANs and Diffusion Models
Autoencoders, VAEs, and Latent Representations
Introduction to physics-informed machine learning

Repository
Open issue

Index

By Kara Lamb

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