Course curriculum

    1. Kickoff

    2. Client Conversation: What are we doing here?

    1. Client Conversation: Importing Data

    2. Importing data into Python with Pandas

    1. Client Conversation: Why do we create a Training and Testing Partition?

    2. Creating a Training and Testing Partition

    1. Client Conversation: Exploring EDA

    2. Getting a Bird's Eye Overview

    3. Vizualizing Distributions with Matplotlib

    4. Why isn't House Price numeric?

    5. Handling Outliers in a Numeric Target Variable

    6. What's happening with all the pubs?

    7. Analysing Categorical Features

    8. Finding relationships between features using Pearsons Correlation

    9. Is the Post Code driving value?

    10. Working with Dates

    1. Client Conversation: Fixing up the data

    2. Build Preprocessing Function

    3. Preview Preprocessed Data

    4. Clean up Analysis Features

    5. Create X and y values

    1. Client Conversation: When are we getting to the Machine Learning?

    2. Import ML Dependencies

    3. Building ML Pipelines with Sklearn Pipelines

    4. Building Hyperparameter Tuning Grids

    5. Train models and perform HPO

About this course

  • $99.00
  • 46 lessons
  • 5 hours of video content

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