Data Processing and Model Training Pipeline for Deep Learning Applications
Data Preparation Begin by creating a duplicate of the original dataset to prevent contamination. Identify missing values using visualizations like heatmaps, and remove redundant fields. import numpy as np import pandas as pd # Find symmetric difference between two lists list_a = ["tom",&qu...