(Don't read this page. It is a work in progress for a Fall'19 graduate automated SE subject at NC State. Come back in mid-October!)

Start 1.preface 2.why se 4 ai? 3.tools 4.ethics: how

Tools baselines Data mining: discretization basic advanced Optimizers: landscapes basic advanced optimizing+data mining Theorem provers: basic advanced

Process requirements collect cleanse label train eval deploy monitor

Code config tests

Exercises 1 2 3a 3b 3c 3d 4

Data collection

---

Sometimes other people’s data is better than yours (the github exaple from mitch)

warnings: transfer elarning. negativ transfer

but when this workits amaizing. the fact that there is some generality across all these dderenfe projects is.. inspriiring.

”””

---

© 2019 timm + zimm