/Air-quality-analysis

Analyzed air quality by studying various atmospheric gasses, assessing pollution levels across cities. Employed machine learning for robust insights, categorizing pollution (good, moderate, unhealthy).

Primary LanguageJupyter Notebook

Air Quality Trend Analysis (ML)

Analyzed air quality by studying various atmospheric gasses and assessing city pollution levels. Employed machine learning for robust insights, categorizing pollution intensity (good, moderate, unhealthy).

  1. Analyzed and preprocessed air quality data using Python, Pandas, Seaborn, and Matplotlib.
  2. Conducted data cleaning, outlier handling, and feature engineering for enhanced dataset quality.
  3. Utilized machine learning for missing value estimation, leveraging parameter correlations.
  4. Implemented standard scaling and labelled encoding.
  5. Generated visualizations for comprehensive insights, including heat maps and scatter plots.

Dataset: https://drive.google.com/file/d/1NGzRs3YFzirZ7TH6YA3YI9NId7fJ29OY/view?usp=sharing