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Duration 7 hours
Course Outline
Introduction to ML in Financial Services
- Survey of prevalent financial ML use cases.
- Advantages and obstacles of ML within regulated industries.
- Overview of the Azure Databricks ecosystem.
Preparing Financial Data for ML
- Ingesting data from Azure Data Lake or database sources.
- Data cleansing, feature engineering, and transformation processes.
- Conducting exploratory data analysis (EDA) within notebooks.
Training and Evaluating ML Models
- Data partitioning and algorithm selection strategies.
- Training regression and classification models.
- Assessing model performance using domain-specific financial metrics.
Model Management with MLflow
- Recording experiments through parameters and performance metrics.
- Storing, registering, and versioning models effectively.
- Ensuring reproducibility and comparing model outcomes.
Deploying and Serving ML Models
- Packaging models for batch processing or real-time inference.
- Serving models via REST APIs or Azure ML endpoints.
- Embedding predictions into financial dashboards or alert systems.
Monitoring and Retraining Pipelines
- Scheduling routine model retraining with updated data.
- Tracking data drift and maintaining model accuracy.
- Automating end-to-end workflows using Databricks Jobs.
Case Study: Financial Risk Scoring
- Developing a risk scoring model for loan or credit applications.
- Interpreting predictions to ensure transparency and compliance.
- Deploying and testing the model in a controlled environment.
Requirements
- A solid grasp of fundamental machine learning principles.
- Practical experience with Python and data analysis techniques.
- Knowledge of financial datasets or reporting structures.
Target Audience
- Data scientists and ML engineers operating in financial services.
- Data analysts seeking to transition into ML roles.
- Technology professionals implementing predictive solutions within finance.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customised Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from £1600 + VAT*
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