Lecture 4

April 11, 2019

Overview

Process of building ML pipeline
- Gathering data
- Extracting features
- Developing model
- Training and optimization
- Evaluation
Sample dataset and code
- Multi-label classification on text data
- Jupyter notebook through the pipeline

Lecture Slides

CMPS290T_S19_L04

Lecture Video

Resources

Slides [Link]
Video [Link]
Colab Notebook [Link]
Machine Learning Crash Course by Google [Link]
ML basics from Deep Learning book [Link]
Scikit-learn [Link]
NLTK [Link]
Gensim [Link]

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