The 'Delivery Time Prediction' folder contains the linear regression model build to predict the delivery time on the basis of the sorting time.It also contains the required dataset as well the a presentation for the same purpose. The main objective of this project is to develop a predictive model for estimating delivery times based on sorting time to enhance operational efficiency in the delivery process. Sorting time - In the context of the delivery business, "sorting time" typically refers to the amount of time it takes for a delivery service to organize and arrange packages or items for dispatch or distribution. Sorting is a crucial step in the logistics process, especially in large distribution centers or warehouses where numerous packages need to be sorted based on their destination or delivery route. The Linear regression model build is very easily able to predict the delivery time on the basis of sorting time but still there might be some exceptions. As the delivery time might differ for regardless having same sorting time. As there might be some other factor which might affect the delivery time.
The scatter plot and pair plot help visualize the relationship between sorting time and delivery time. The linear regression model is trained on the data to predict delivery time based on sorting time. Evaluation metrics such as Mean Absolute Error, Mean Squared Error, and Root Mean Squared Error are used to assess the model's performance. The regression line plot shows the fitted line on the test data, and the residual plot helps assess the model's performance in predicting delivery time.
The 'Salary Hike Prediction' folder contains the linear regression model build to predict the salary hike for an employee on the basis of years of experience. It also contains the required dataset as well the a presentation for the same purpose. Objective: To develop a predictive model for estimating salary hikes for employees based on their years of experience. Why: Enhance the accuracy and fairness of salary adjustments, providing a data-driven approach to decision-making. Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. In the context of predicting salary based on years of experience, linear regression helps us understand and quantify the linear relationship between these two variables.