Writer's Block? RNNs Can Help!

from pathlib import Path

DATA_DIR = Path("/kaggle/input")
if (DATA_DIR / "ucfai-core-sp20-recurrent-nets").exists():
    DATA_DIR /= "ucfai-core-sp20-recurrent-nets"
    # 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-sp20-recurrent-nets/data
    DATA_DIR = Path("data")

Other Meetings in this Series

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Ever wonder how Facebook tells you which friends to tag in your photos, or how Siri can even understand your request? In this meeting we'll dive into convolutional neural networks and give you all the tools to build smart systems such as these. Join us in learning how we can grant our computers the gifts of hearing and sight!

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It's time to put what you have learned into action. Here, we have prepared some datasets for you to build a a model to solve. This is different from past meetings, as it will be a full workshop. We provide the data sets and a notebook that gets you started, but it is up to you to build a model to solve the problem. So, what will you be doing? We have two datasets, one is using planetary data to predict if a planet is an exoplanet or not, so your model can help us find more Earth-like planets that could contain life! The second dataset will be used to build a model that mimics a pokedex! Well, not fully, but the goal is to predict the name of a pokemon and also predict its type (such as electric, fire, etc.) This will be extremely fun and give you a chance to apply what you have learned, with us here to help!

Contributing Authors

John Muchovej
John Muchovej

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