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- Find an answer to your question in the Udacity FAQ
- Learn about different parts of the Classroom in Udacity Introduction

Contents

- 1 Course Resources
- 1.1 Reading Materials
- 1.1.1 Suggested Text
- 1.1.2 Optional Text
- 1.1.3 Reading List

- 1.2 Coding Resources
- 1.3 Downloadable Materials

- 1.1 Reading Materials
- 2 Course Syllabus
- 2.1 Lesson 1: Decision Trees
- 2.2 Lesson 2: Regression & Classification
- 2.3 Lesson 3: Neural Networks
- 2.4 Lesson 4: Instance Based Learning
- 2.5 Lesson 5: Ensemble B&B
- 2.6 Lesson 6: Kernel Methods & SVMs
- 2.7 Lesson 7: Comp Learning Theory
- 2.8 Lesson 8: VC Dimensions
- 2.9 Lesson 9: Bayesian Learning
- 2.10 Lesson 10: Bayesian Inference

- Tom Mitchell, Machine Learning. McGraw-Hill, 1997.
- Ethem AlpaydÄ±n, Introduction to Machine Learning. Second Edition.

- Larry Wasserman, All of Statistics. Springer, 2010.
- Richard Sutton and Andrew Barto, Reinforcement Learning: An introduction. MIT Press, 1998.
- Trevor Hastie, Robert Tibshirani and Jerome Friedman, The Elements of Statistical Learning. Springer, 2009.

- Linear Algebra
- Support Vector Machines
- Deep Learning
- Boosting
- Information Theory
- Optimization
- Dimensionality Reduction
- Unsupervised Learning
- Markov Decision Processes
- Game Theory

- Optimization
- Clustering
- Feature Selection and Transformation
- Information Theory

- Markov Decision Processes
- Reinforcement Learning
- Game Theory

- WEKA Machine learning software in JAVA that you can use for your projects
- Data Mining with Weka A MOOC Course
- ABAGAIL Machine learning software in JAVA. This is hosted on my github, so you can contribute too
- scikit-learn A popular python library for supervised and unsupervised learning algorithms
- MATLAB NN Toolbox The toolbox supports supervised learning with feedforward, radial basis, and dynamic networks and unsupervised learning with self-organizing maps and competitive layers.
- Murphy's MDP Toolbox for Matlab
- MATLAB Clustering Package By Frank Dellaert
- ICA Example

- UCI Machine Learning Repository An online repository of data sets that can be used for machine learning experiments.
- Stanford Large Network Dataset Dataset of large social and information networks.
- Vision Benchmark Suite Autonomous car dataset
- Other datasets

You can download Supplemental Materials, Lesson Videos and Transcripts from Downloadables (bottom right corner of the Classroom) or from the Dashboard (first option on the navigation bar on the left hand side).