This case helps the learner to apply supervised machine learning techniques (Linear Regression) for predicting the price of used cars.
Understand key insights about the data by implementing various univariate & bivariate visualization methods.
Deep-dive to the concept of data cleaning techniques such as missing value treatment and outlier treatment to improve predictive power of Machine learning models.
Working understanding of feature engineering technqiues such as one hot encoding to convert categorical data to numerical data, as most algorithms do not support categorical input.
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Difficulty: Advanced
Duration: Approximately 3 hours
