Advanced Configuration Modules Series

Description: Join Hayley to dive deeper into advanced configuration settings for machine learning models. Configuring a machine learning model can be a critical step in harnessing its true potential. One AI does an excellent job assisting in building models, but sometimes, it doesn’t get everything quite right. By digging into settings such as dimensionality reduction, estimator configuration, upsampling, and per column interventions, users can tailor their models to extract maximum insights from their data. This customization isn't just about fine-tuning performance, but also enhances the relevance and accuracy of predictions which helps in finding actionable insights. The modules do not need to be watched in any particular order and you can skip around as you please.

Module Type: Functional function sym.png & Foundational foundation sym.png

Level: Advanced I-Spaceship.svg

Audience: Model creators & managers

Prerequisites: "Data Preprocessing", "One AI Recipes", "One AI Exploratory Data Analysis (EDA) Report", "One AI Results Summary", & "Model Refinement" modules.  The "Global Settings Module Series" may also be helpful, but is not explicitly required.  

Run time: ~10-15 minutes per module

All transcripts can be found attached at the bottom of the page.

 

Dimensionality Reduction

Module Sections:

00:00 - Intro, Topics Covered, & Learning Outcomes

01:27 - Dimensionality & Dimensionality Reduction Overview

04:54 - Dimensionality Impacts on Models

07:16 - Configuration Options in One AI

10:20 - Default Configuration in One AI

11:02 - Configuring Dimensionality Reduction in One AI

13:32 - Conclusion & Thanks

 

Estimator Configuration

Module Sections:

00:00 - Intro, Topics Covered, & Learning Outcomes

01:18 - Overview of Estimators

02:37 - Estimators Available in One AI

02:54 - Estimators Available in One AI: Classification Estimators

06:23 - Estimators Available in One AI: Regression Estimators

10:25 - Default Settings in One AI

12:10 - Estimator Configuration in One AI

13:32 - Conclusion & Thanks

 

Upsampling

Module Sections:

00:00 - Intro, Topics Covered, & Learning Outcomes

01:20 - Overview & Significance of Upsampling

04:09 - Methods & Ratios Available in One AI

07:15 - Default Settings in One AI

07:41 - Configuring Upsampling in One AI

09:02 - Conclusion & Thanks

 

Per Column Interventions

Module Sections:

00:00 - Intro, Topics Covered, & Learning Outcomes

01:22 - Per Column Intervention Overview

03:15 - Per Column Interventions Available in One AI

07:22 - Configuring in One AI

08:59 - Conclusion & Thanks

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