A collection of data science related explainers geared towards fulfilling homework requirements for ASU's MAT 422 class.
- 1.2 Elements of Linear Algebra
- 1.3 Linear Regression
- 1.4 Principal Component Analysis
- 2.2 Probability Distributions
- 2.3 Independent Variables and Random Samples
- 2.4 Maximum Likelihood Estimation
- 3.2 Continuity & Differentiation
- 3.3 Unconstrained Optimization
- 3.4 Logistic Regression
- 3.5 K Means & 3.6 Support Vector Machines
- 3.7 Neural Networks
- [4.1 Graphs]
- 4.2 Spectral Graph Bipartitioning