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This is a python project for building a linear regression model that is used to predict used car prices from a given dataset using machine learning. The dataset used for this project is taken from Kaggle. For the complete video explanation, check out the following link.
This project demonstrates how to perform exploratory data analysis on car price prediction dataset. The dataset is available on Kaggle and consists of various attributes related to the sales price of used ford cars. We will be performing Exploratory Data Analysis to understand this data and to find out which factors affect the sales price of use…
This project explains on how to build a machine learning algorithm for calculating the medical insurance costs. Check out my video on this topic for the complete video explanation.
This project demonstrates how to implement k-means clustering on unsupervised data. The dataset used here is the famous iris dataset. To see a complete video explanation on this topic, check out the attached link.
This python project explains on how to implement a supervised machine learning algorithm on the famous iris dataset. The different classifiers used in this project includes decision tree and k-nearest neighbors. For a complete explanation of this project, check out my video on this topic.