- This page is currently under construction.
- The university learning platform LEA is still the official source of information.
- Testing with classroom.github.com is being done to see if it helps manage the projects for this course.
####Topics (taken from 2015 summer semester slide titles):
- Introduction to Learning and Adaptivity
- Concept Learning
- Decision Tree Learning
- Biological Neural Networks
- Artificial Neural Networks
- Self-Organizing Maps
- Reinforcement Learning
- Genetic Algorithms
Additional Topics covered in Alpaydin Book "Introduction to Machine Learning", slides available online
https://www.cmpe.boun.edu.tr/~ethem/i2ml2e
- Introduction
- Supervised Learning
- Bayesian Decision Theory
- Parameteric Methods
- Multivariate Methods
- Dimensionality Reduction
- Clustering
- Nonparametric Methods
- Decision Trees
- Linear Discrimination
- Multilayer Perceptrons
- Local Models
- Kernel Machines
- Bayesian Estimation
- Hidden Markov Models
- Graphical Models
- Combining Multiple Learners
- Reinforcement Learning
- Design and Analysis of Machine Learning Experiments
https://alex.smola.org/drafts/thebook.pdf svn:https://[email protected]/thebook/trunk/Book/thebook.tex
Everyone hates getting a bunch of newsletter mail, but I hightly recommend signing up to some of the nvidia newsletters. https://www.nvidia.com/object/newsletter.html, even if you don't have an Nvidia GPU they're often sharing very interesting articles and projects for Machine Learning, and Robotics.
- https://www.nvidia.com/object/machine-learning.html
- https://developer.nvidia.com/deep-learning
- https://developer.nvidia.com/deep-learning-software
If you have an Nvidia GPU and are using 14.04, check out their DIGITS project.