: 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"
    # 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

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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.

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We'll take what we learned last week and actually write up a Neural Network to train on the MNIST dataset, to recognize hand-written digits with about 92% accuracy.

Contributing Authors

John Muchovej
John Muchovej

Founder of AI@UCF. Researcher in cognitive science and machine learning. Focusing on intuitive physics and intuitive psychology.