Data Analysis and Machine Learning: Introduction and Representing data
Contents
What is Machine Learning?
Types of Machine Learning
Different algorithms
Software and needed installations
Python installers
Installing R, C++, cython or Julia
Installing R, C++, cython or Julia
Introduction to Jupyter notebook and available tools
Representing data, more examples
Predator-Prey model from ecology
Case study from Hudson bay
Hudson bay data
Plotting the data
Hares and lynx in Hudson bay from 1900 to 1920
Why now create a computer model for the hare and lynx populations?
The traditional (top-down) approach
Basic mathematics notation
Basic dynamics of the population of hares
Basic dynamics of the population of lynx
Evolution equations
Adapt the model to the Hudson Bay case
The program
The plot
Linear regression in Python
Linear Least squares in R
Non-Linear Least squares in R
Hares and lynx in Hudson bay from 1900 to 1920
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