In this repository I go over some case-studies that involve the deployment of machine/deep learning algorithms in Python in order to train and evaluate models on both synthetic and real datasets.
| Tool/Algorithm | Application |
|---|---|
| Linear Regression | E-commerce data analytics |
| Logistic Regression | Ad click prediction |
| Multivariate Gaussian | Anomaly Detection for network servers |
| Polynomial/Linear Regression | Audio prediction |
| Principal Component Analysis | Dimensionality reduction for simple 2D dataset |
| Bayesian Linear Regression | Prediction of burnt calories from exercise length |
| Bayes Factor/Marginal Likelihood | Bayesian Model selection for coin toss |
| Gaussian Process | Regression with confidence interval |
| Regularized Linear Regressions | Predicting of Computerised Tomography slice location |