PAC Learning

Online Learning

Stochastic gradient descent (SGD)

Decision Trees

Clustering

Error Decomposition

Boosting

Decision Making

Gradient descent

Similarity Learning

Neural Networks Learning

Mathematical Optimization

Multiclass Learning

Neural network

COS 324 - Introduction to Machine Learning Princeton University Fall 2017 A thorough introduction to machine learning principles such as online learning, decision making, gradient-based learning, and empirical risk minimization. It also explores regression, classification, dimensionality reduction, ensemble methods, neural networks, and deep learning. The course material is self-contained and based on freely available resources. The course provides an introduction to machine learning.

**Topic covered**:

- Online learning and decision making
- Learning from examples and generalization
- Empirical risk minimization and regularization
- Introduction to convex analysis
- Gradient-based learning
- Implementation and analysis of learning algorithms for regression, binary classification, multiclass categorization, and ranking problems
- Dimensionality reduction methods
- Ensemble methods and boosting
- Neural networks and deep learning
- Markov decision precesses    **NOTICE:**  All material of the course is self-contained and based on freely available books and surveys.   
Main references:

- [Understanding Machine Learning: From Theory to Algorithms](http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/), by Shai Shalev-Shwartz and Shai Ben-David
- [Online convex optimization](http://ocobook.cs.princeton.edu/), by Elad Hazan
- [Machine Learning](http://www.cs.cmu.edu/afs/cs.cmu.edu/user/mitchell/ftp/mlbook.html), by Tom Mitchell
- An Introduction to Computational Learning Theory, by Michael Kearns &amp; Umesh Vazirani
- Machine Learning: A Probabilistic Perspective, by Kevin Murphy,

Further advanced references: - [Convex Optimization](http://stanford.edu/~boyd/cvxbook/), by Stephen Boyd and Lieven Vandenberghe
- [Convex optimization: algorithms and complexity](https://arxiv.org/abs/1405.4980), by Sebastien Bubeck
- Artificial Intelligence: A Modern Approach, by Stuart Russell and Peter Norvig

Python Tutorials - [An interactive python tutorial](https://learnpython.org/) from LearnPython.com
- [Tutorial for Python 2.7](https://docs.python.org/2.7/tutorial/) from python.org
- [Tutorial for Python 3](https://docs.python.org/3/tutorial/) from python.org

COS 324 - Introduction to Machine Learning

Machine Learning

Probably approximately correct learning

PAC Learning

1 courses cover this concept

COS 324 - Introduction to Machine Learning