Real-World CV Project Walkthrough

1 📋

Project Planning

Define objectives, scope, and success metrics for your CV application

• Requirements gathering
• Problem definition
• Success metrics
• Resource planning

2 🗃️

Data Preparation

Collect, annotate, and prepare high-quality training data

• Data collection strategy
• Annotation tools & process
• Data preprocessing
• Augmentation pipeline

3 🏗️

Model Selection

Choose the right architecture and approach for your specific problem

• Architecture comparison
• Transfer learning setup
• Baseline establishment
• Performance benchmarks

4 ⚙️

Training Pipeline

Implement robust training with monitoring and optimization

• Training infrastructure
• Hyperparameter tuning
• Progress monitoring
• Model checkpointing

5 📊

Evaluation & Testing

Thoroughly evaluate model performance and handle edge cases

• Metrics selection
• Validation strategy
• Error analysis
• Edge case testing

6 🚀

Deployment

Deploy to production with optimization and monitoring

• Model optimization
• API development
• Scaling strategy
• Monitoring setup