Digitalization
===

###### tags: `SciML-Lecture`

## Introduction

- [ ] Bayesian Curve Fitting
- [ ] Maximum Likelihood
- [ ] Clean up Examples, and expand them more s.t. one can see the techniques behind them

## [Core Content 1](https://hackmd.io/RVkALsMHTqehvfiqCBvklg):

- [ ] Linear Regression
- [ ] Logistic Regression
- [ ] Classification
- [ ] Exponential Family
- [ ] Bayesian Linear & Logistic Regression (From Old Tutorials)

## [Core Content 3](https://hackmd.io/j104Zu4pRD-YMjoHdoOXrg):

- [ ] Kernel Methods
- [ ] Support Vector Machines
- [ ] Gaussian Processes

# New Content

## [Core Content 1](https://hackmd.io/ZqG8ZQy2TQebvQ2rHYpUng):

- [ ] Sufficient Statistics
- [ ] Exponential Family
- [ ] Bayesian Inference

## [Core Content 2](https://hackmd.io/NAdWxG1FT2GYd02wcfq7aA):

- [ ] Optimization
- [ ] Cost Functions
- [ ] Least Squares
- [ ] MLE
- [ ] Overfitting
- [ ] Regularization

## [Core Content 4](https://hackmd.io/2MXaFB4lQfieQ__3YuLmDw):

- [ ] Artificial Neural Networks
- [ ] Convolutional Neural Networks
- [ ] Recurrent Neural Networks
- [ ] Backpropagation