Thank you for sending your enquiry! One of our team member will contact you shortly.
Thank you for sending your booking! One of our team member will contact you shortly.
Course Outline
Introduction
- Why extract rules from data?
Overview of Sklearn Modules (Decision Tree/Random Forrest)
Installing and Configuring skope-rules
Case Study: Detecting Credit Default Rates
Importing Data
Using SkopeRules for Imbalanced Classification
Training the SkopeRules Classifier
Extracting the Rules
Fusing the Rules
Fitting Classification and Regression Trees to Sub-samples
Selecting Higher Precision Rules
Testing Higher Precision Rules
Summary and Conclusion
Requirements
- Python programming experience
- Knowledge of machine learning algorithms
Audience
- Developers
Testimonials
Giving many practical examples
Monika Borowska, Polska Spółka Gazownictwa sp. z o.o.
wiedza praktyczna trenera
Waldek - Monika Borowska, Polska Spółka Gazownictwa sp. z o.o.
Related Courses
Python Security
14 hours
From Zero to AI
35 hours
IBM ODM Decision Management
21 hours
UAE Corporate Tax
7 hours
Managing Business Logic with Drools
21 hours
Drools Rules Administration
21 hours
OptaPlanner in Practice
21 hours
jBPM and Drools
14 hours