Introduction to Machine Learning
summary
Hands-on demo trains a decision forests classifier in Colab with pandas and TensorFlow to predict Palmer Penguins species, starting from 344 rows, dropping nulls and the ambiguous year field to 333 usable rows, splitting ~75/25 for training/testing. The model trains in under a second, visualizes individual trees and feature splits (flipper length, bill depth, island) in TensorBoard, and achieves about 96% accuracy, so the pipeline works end to end.
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chapters (22)
- 0:00Introduction
- 0:35Collab
- 1:00Welcome
- 2:00Agenda
- 3:00What is Machine Learning
- 6:30The Data Set
- 8:30Decision Trees
- 11:05Data
- 20:25Labels
- 21:35Training vs Testing Data
- 22:30Good News
- 23:00Training
- 23:50Evaluation
- 24:55Visualizations
- 27:45Tree Accuracy
- 29:55Different Models
- 31:15Free Resources
- 34:05Questions
- 38:29Common Steps
- 39:47Simple ML
- 41:29UX Research
- 43:19Advice
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