How Computers Can See and Other Ways Machines Can Think

from pathlib import Path

DATA_DIR = Path("/kaggle/input")
if (DATA_DIR / "ucfai-core-sp19-conv-nets").exists():
    DATA_DIR /= "ucfai-core-sp19-conv-nets"
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-sp19-conv-nets/data
    DATA_DIR = Path("data")

Other Meetings in this Series

: Getting Started With Neural Networks

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You've heard about them: Beating humans at all types of games, driving cars, and recommending your next Netflix series to watch, but what ARE neural networks? In this lecture, you'll actually learn step by step how neural networks function and how they learn. Then, you'll deploy one yourself!

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This lecture is all about Recurrent Neural Networks. These are networks with with added memory, which means they can learn from sequential data such as speech, text, videos, and more. Different types of RNNs and strategies for building them will also be covered. The project will be building a LSTM-RNN to generate new original scripts for the TV series “The Simpsons”. Come and find out if our networks can become better writers for the show!

Contributing Authors

John Muchovej
John Muchovej

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