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Duration 7 hours
Course Outline
Introduction to Machine Learning in Financial Services
- Survey of typical machine learning applications in finance
- Advantages and complexities of implementing ML in regulated sectors
- Overview of the Azure Databricks ecosystem
Preparing Financial Data for Machine Learning
- Acquiring data from Azure Data Lake or database sources
- Performing data cleansing, feature engineering, and transformations
- Conducting exploratory data analysis (EDA) using notebooks
Training and Assessing Machine Learning Models
- Data partitioning and selection of appropriate machine learning algorithms
- Training regression and classification models
- Assessing model efficacy using industry-specific financial metrics
Model Management via MLflow
- Monitoring experiments by tracking parameters and performance metrics
- Storing, registering, and managing model versions
- Ensuring reproducibility and facilitating the comparison of model outcomes
Deployment and Serving of Machine Learning Models
- Preparing models for batch processing or real-time inference scenarios
- Serving models through REST APIs or Azure ML endpoints
- Embedding predictive insights into financial dashboards or alert systems
Monitoring and Retraining Pipelines
- Automating periodic model retraining with updated data streams
- Tracking data drift and maintaining model accuracy
- Automating end-to-end workflows using Databricks Jobs
Practical Walkthrough: Financial Risk Scoring
- Developing a risk scoring model for loan or credit assessments
- Interpreting predictions to ensure transparency and regulatory compliance
- Deploying and validating the model within a controlled testing environment
Requirements
- Fundamental understanding of core machine learning principles.
- Practical experience with Python and data analysis techniques.
- Working knowledge of financial datasets or reporting standards.
Target Audience
- Data scientists and machine learning engineers working within financial services.
- Data analysts looking to transition into machine learning-focused roles.
- Technology professionals responsible for implementing predictive solutions in the finance industry.
