Description
Data Collection: Identify and Collect data from various web sources via web scraping for model training purpose.
Data Organization: Filter the obtained, clean it and prepare it for model training.
Model Prototyping: Theorize, search and code the model architectures relevant to specific problem at hand.
Model Training: Define network architecture and write the corresponding utility functions for training the model.
Metric Definition: Create a metric to evaluate the model based on the provided problem statement.
Model Testing: Test the trained mode using this defined metric.