This packet predicts the Air Quality Index for Pollution Control using Linear Regression with the help of a machine learning technique in Python.

OBJECTIVE:

The aim of this project is to predict the Air Quality Index using Machine Learning.

The dataset consists of air samples of different locations in Delhi. We are required to design a Machine Learning model to predict the Air Quality Index using this data.

PROJECT:

In this project, we predict the Air Quality Index of Delhi by using Linear Regression. I have used the Python language and Jupyter Notebook Editor. We train the model using the training data set which contains 5 feature columns and 1 target column. We then make use of feature analysis for the prediction of testing data. The testing data consists of 5 feature columns and our model has to predict the target column. We conclude by calculating the accuracy of the model.

LIBRARIES:

NumPy, Pandas, Sklearn and Matplotlib

NumPy: NumPy, which stands for Numerical Python, is a multidimensional array library of Python which is used for scientific computing.

Pandas: Pandas is a Python library that provides data manipulation tools for data analysis. Using this library, we can read a CSV file which is a data set for the model.

Sklearn: Sklearn is one of the most helpful libraries in Python which features various algorithms for Machine Learning models such as Classification, Regression, Clustering, etc.

Matplotlib: Matplotlib is a data visualization library that is used for plotting charts like bar plots, scatter plots, histograms, etc. We can use this library by using the ‘import matplotlib.pyplot’ command.

Submitted by Shravya Chinta (shravyachinta)

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