# : an Intro to Neural Networks (ANNs)

from pathlib import Path

DATA_DIR = Path("/kaggle/input")
if (DATA_DIR / "ucfai-core-sp18-neural-nets-lecture").exists():
DATA_DIR /= "ucfai-core-sp18-neural-nets-lecture"
else:
# You'll need to download the data from Kaggle and place it in the data/
#   directory beside this notebook.
# The data should be here: https://kaggle.com/c/ucfai-core-sp18-neural-nets-lecture/data
DATA_DIR = Path("data")


## Other Meetings in this Series

#### Welcome Back to SIGAI, Featuring Gradient Descent

Welcome back to SIGAI! We'll be covering some administrative needs – like how we're doing lectures/workshops and what we expect of coordinators, since we'll have elections in March. Then we'll go over some math to check everyone's background so you're uber prepared for next week! Once we've covered that, we'll go over Gradient Descent and get a rough idea of how it works – this is integral to almost all our content this semester.