ML Pipeline
ML Pipeline on AI-ML Companion: Complete ML workflow from raw data to production deployment. 15 interactive modules with live visualizations, quizzes, and hands-on Python coding.
Start free: Data Collection is fully open to everyone, no account required. The other 14 modules are part of AI-ML Companion Premium; every title and summary is listed below so you can see exactly what the track covers before deciding.
Modules in this track
- Data Collection (free) - Gathering quality data from various sources
- EDA Fundamentals (premium) - Exploratory Data Analysis techniques
- EDA Visualization (premium) - Visual patterns and insights
- Data Preprocessing (premium) - Cleaning and preparing data
- Feature Engineering (premium) - Creating powerful features
- Feature Selection (premium) - Choosing the right features
- Data Splitting (premium) - Train, validation, test sets
- Model Selection (premium) - Choosing the right algorithm
- Model Training (premium) - Training and fitting models
- Hyperparameter Tuning (premium) - Optimizing model parameters
- Model Evaluation (premium) - Metrics and validation
- Model Interpretation (premium) - Understanding model decisions
- Deployment (premium) - Putting models into production
- Monitoring & MLOps (premium) - Maintaining models in production
- Project: Credit Risk Pipeline (premium) - Build a production ML pipeline from messy bank data to deployed credit risk model - synthesizing every stage from EDA to monitoring