Exploratory Data Analysis (EDA) is an approach to analyse the data using visual techniques. It is used to discover trends, and patterns, or to check assumptions with the help of statistical summaries and graphical representations. Machine learning is a growing technology that enables computers to learn automatically from past data. Deep learning is a subset of machine learning that can automatically learn and improve functions by examining algorithms.
Air is what keeps humans alive. Since industrialization, there has been an increasing concern about environmental pollution. As mentioned in the WHO report 7 million premature deaths annually are linked to air pollution, air pollution is the world’s largest single environmental risk. Moreover, as reported in the NY Times article, India’s Air Pollution Rivals China’s as World’s Deadliest, it has been found that India’s air pollution is deadlier than even China’s.
Monitoring it and understanding its quality is of immense importance to our well-being. Using this dataset one can explore India’s air pollution levels at a more granular scale.
Researching, identifying and gathering potential datasets
Machine learning modelling to predict future AQI based on input features
Testing model and deploying on cloud
Exploratory Data Analysis, Data Visualization, project management, communication, and Machine Learning, Deep Learning