The content is the implemention of the following core algorithms in statistical computing using R, Python and C++. All the codes avoid the built-in packages and give an insight into the algorithm.
The topics includes:
- Least squares regression, sweep operator, QR decomposition
- Eigen computation, Principal Component Analysis
- Logistic regression, Newton-Raphson
- Lasso, coordinate descent, boosting, solution path
- Feed-forward neural network, back-propagation
- EM algorithm, Gaussian mixture, factor analysis
- Random number generators, Monte Carlo integration
- Metropolis algorithm, Gibbs sampling, Bayesian posterior sampling