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from pathlib import Path

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

Other Meetings in this Series

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Ever wonder how Facebook can tell you which friends to tag in your photos or how Google automatically makes collages and animations for you? This lecture is all about that: We'll teach you the basics of computer vision using convolutional neural networks so you can make your own algorithm to automatically analyze your visual data!

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Some of the hardest aspects of Machine Learning are the details. Almost every algorithm we use is sensitive to "hyperparameters" which affect the initialization, optimization speed, and even the possibility of becoming accurate. We'll cover the general heuristics you can use to figure out what hyperparameters to use, how to find the optimal ones, what you can do to make models more resilient, and the like. This workshop will be pretty "down-in-the-weeds" but will give you a better intuition about Machine Learning and its shortcomings.

Contributing Authors

John Muchovej
John Muchovej

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