📈 Proposed Solutions for the project of the Machine Learning Curricular Unit @FEUP
Business Understanding
- Determine business Objectives
- Assess Situation
- Determine Data Mining Goals
- Produce Project Plan
Data Understanding
- Collect Initial Data
- Describe Data
- Explore Data
- Verify Data Quality
Data Preparation
- Select Data
- Clean Data
- Construct Data
- Integrate Data
- Format Data
Modeling
- Select Modeling Techniques
- Generate Test Design
- Build Model
- Assess Model
Evaluation
- Evaluate Results
- Review Process
- Determine Next Steps
Deployment
- Plan Deployment
- Plan Monitoring and Maintenance
- Produce Final Report
- Review Project
Business Understanding
- analysis of requirements with the end user
- definition of business goals
- translation of business goals into data mining goals
Data Understanding
- diversity of statistical methods
- complexity of statistical methods
- interpretation of results of statistical methods
- knowledge extraction from results of statistical methods
- diversity of plots
- complexity of plots
- presentation
- interpretation of plots
- visual knowledge extraction
Data Preparation
- data integration
- assessment of dimensions of data quality
- cleaning (redundancy, missing data, outliers)
- data transformation for compatibility with algorithms
- feature engineering from tabular data
- sampling for domain-specific purposes
- sampling for development
- imbalanced data
- feature selection
Descriptive
- diversity of algorithms
- parameter tuning
- understanding algorithm behavior
- performance measure
- correct interpretation of performance measures
- comparative analysis of results
- model improvement
- analysis of results
Predictive
- diversity of tasks
- diversity of algorithms
- parameter tuning
- understanding algorithm behavior
- performance estimation (training vs test, other factors (e.g. time), perfomance measure, correct interpretation of performance measures, analysis of results)
- model improvement
- feature importance
- analysis of "white-box" models
Project Management
- methodology
- plan
- PM tools
- collaboration tools
Tools
- analytics
- database
- other tools (e.g. data cleaning, visualization)
Presentation
- quality of layout
- quality of content in slides
- delivery
- use of time