: Building an Extensible ANN

from pathlib import Path

DATA_DIR = Path("/kaggle/input")
if (DATA_DIR / "ucfai-core-sp18-neural-nets-workshop").exists():
    DATA_DIR /= "ucfai-core-sp18-neural-nets-workshop"
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-workshop/data
    DATA_DIR = Path("data")

Other Meetings in this Series

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Here, we'll dive, head first, into the nitty-gritty of Neural Networks, how they work, what Gradient Descent achieves for them, and how Neural Networks act on the feedback that Gradient Descent derives.

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Contributing Authors

John Muchovej
John Muchovej

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