Practice Makes Permanent, but Data's Messy

John Muchovej
Last updated on Feb 19, 2023
1 min read 
from pathlib import Path

DATA_DIR = Path("/kaggle/input")
if (DATA_DIR / "ucfai-core-fa18-practicing-data-cleaning").exists():
    DATA_DIR /= "ucfai-core-fa18-practicing-data-cleaning"
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-fa18-practicing-data-cleaning/data
    DATA_DIR = Path("data")

Other Meetings in this Series

Aidan Lakshman
Nov 7, 2020 4:30 PM
PSY 105
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Support Vector Machines are a simple and powerful classification algorithm that perform well in nearly every situation. They're commonly used in image recognition, face detection, bioinformatics, handwriting recognition, and text categorization. The math behind it is pretty cool, as it relies upon embedding data into higher dimensional space to create linear divisions between categories. SVMs are a great resource to add to your data science toolkit, as they're relatively simple to understand and are also one of the best classification algorithms that do not involve neural networks.

Contributing Authors

John Muchovej
John Muchovej

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