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URL:https://www.learndesk.us/class/6052158501814272/lesson/85d22e20ba42bca721b36e6200dbe5c8?ref=outlook-calendar
SUMMARY:Follow the Likes
DTSTART;TZID=America/Los_Angeles:20260504T190000
DTEND;TZID=America/Los_Angeles:20260504T200000
LOCATION:https://www.learndesk.us/class/6052158501814272/lesson/85d22e20ba42bca721b36e6200dbe5c8?ref=outlook-calendar
DESCRIPTION: - A detailed walkthrough of the code that loads the data
- Introduces the classification problem

Discusses the uses of this technique, including

1. Gender prediction
2. Topic preference
3. Movie genre preference
4. Hashtag preference
5. Magazine article preference
6. Age prediction
7. Psychographic prediction

Introduces the following concepts

1. Classification
2. Area Under Curve (AUC) metric
3. Vectorization
4. Executes code in the console while simultaneously walking through the code in a text editor

Shows how to do the following:

1. Load the dataset
2. Add a schema to the data
3. Clean the data
4. Convert the data to feature vector format
5. Train a classification model on the data
6. Apply a trained classification model to test data
7. Evaluate the accuracy of the trained model

https://www.learndesk.us/class/6052158501814272/lesson/85d22e20ba42bca721b36e6200dbe5c8?ref=outlook-calendar
STATUS:CONFIRMED
SEQUENCE:3
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