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Intermediate Machine Learning

via Kaggle

Overview

Handle missing values, non-numeric values, data leakage, and more.
  • Review what you need for this course.
  • Missing values happen. Be prepared for this common challenge in real datasets.
  • There's a lot of non-numeric data out there. Here's how to use it for machine learning.
  • A critical skill for deploying (and even testing) complex models with pre-processing.
  • A better way to test your models.
  • The most accurate modeling technique for structured data.
  • Find and fix this problem that ruins your model in subtle ways.

Syllabus

  • Introduction
  • Missing Values
  • Categorical Variables
  • Pipelines
  • Cross-Validation
  • XGBoost
  • Data Leakage

Taught by

Alexis Cook

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