Library & Recommended Readings

Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville. Available free online at: https://www.deeplearningbook.org/

Probabilistic Machine Learning (both the Intro and the Advanced topics) by Kevin Murphy

Machine Learning with PyTorch and Scikit-Learn by Sebastian, Yukxi and Vahid

Kernel Methods for Pattern Analysis by Shawe-Taylor and Nello

Reinforcement Learning - An Introduction by Sutton and Barto

Modeling & Reasoning with Bayesian Networks by Adnan

Understanding Machine Learning: From Theory to Algorithms by Shwartz and David

Causal Inference: What If by Robins and Hernan

Convex Optimization by Vandenberghe and Boyd

Regression and Other Stories - Gelman, Hill and Vehtari

Probabilistic Graphical Models by Koller and Friedman

Pattern Recognition and Machine Learning by Bishop

Learning from Data: A Short Course by Lin, Magdon-Ismail and Abu-Mostafa

The Sage Handbook of Remote Sensing by Warner, Nellis and Foody

Environmental Remote Sensing, from Regional to Global Scales by Foody and Curran

Applied Geostatistics by Isaaks and Srivastava

Geospatial Analysis by Smith, Goodchild and Longley.  Available free online at: https://spatialanalysisonline.com/HTML/index.html

GIS Fundamentals by Bolstad

Remote Sensing of the Environment - An Earth Resource Perspective by Jensen

Assessing the Accuracy of Remotely Sensed Data: Principles and Practices by Congalton

People and Pixels, National Research Council. Free at https://nap.nationalacademies.org/catalog/5963/people-and-pixels-linking-remote-sensing-and-social-science

Weathering Risk in Rural Mexico by Eakin

Heat Wave by Klinberg

Automate This by Steiner and Dixon

Thinking Fast and Slow by Kahneman

Environment and Society - Human Perspectives on Environmental Issues by Harper

Because Data Can't Speak for Itself by Chrisinger and Brodsky

Guns, Germs & Steel and/or Collapse by Jared Diamond

Why Nations Fail by Acemohlu and Robinson