Age Detection Model Development

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Here’s a structured approach for your Age Detection Model using pandas, seaborn, and scikit-learn: 1. Data Inspection & Cleaning python Copy code import pandas as pd # Load dataset df = pd.read_csv("") # Inspect dataset print(()) print(()) print(().sum()) # Check for missing values # Handle missing values (example: filling with median values) ((), inplace=True) # Check and remove duplicate rows df.drop_duplicates(inplace=True) 2. Data Visualization python Copy code import seaborn as sns import as plt # Age distribution (df["age"], bins=20, kde=True) () # Pairplot for relationships (if multiple features exist) (df, hue="age") () 3. Train-Test Split & Encoding python Copy code from sklearn.model_selection import train_test_split from impo...

Keyword: Machine Learning

Delivery Time: 2 days left days

Price: $340.0

Data Mining Data Processing Machine Learning (ML) Python Software Architecture