Gaussian Processes for Machine Learning: Book webpage
Carl Edward Rasmussen and Christopher K. I. Williams The MIT Press, 2006. ISBN 0-262-18253-X. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical
R2D3
Table of Contents A Visual Introduction to Machine Learning Part 1: A Decision Tree Part 2: Bias and Variance Misc Design in a World where Machines are Learning Making Sense of COVID-19 Frequently Asked Questions R2D3 is an experiment in expressing statistical thinking with interactive design. Find us at @r2d3us. Questions? Check out the FAQs. Stephanie interprets R2 Stephanie is currently at Netf
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Forecasting Time Series data with Prophet - Trend Changepoints - Python Data
Forecasting Time Series data with Prophet - Part 3 - Python Data
Forecasting Time-Series data with Prophet - Part 2 - Python Data
Forecasting Time-Series data with Prophet - Part 1 - Python Data
RPubs - Demo of the use of R and Python for credit risk score model
Statistics and risk modelling using Python
Lisha Li
