This analysis is based on a dataset containing the age, gender and annual salary of people interested in buying in car and whether or not they bought the car. The data is used to train a model to help predict if future customers will buy the car or not. The model trained can be used to predicted whether or not someone will purchase a car based on their age and annual salary. This can be useful in a number of ways. For example, a car dealership can use this model to predict whether a potential customer is likely to purchase a car based on their age and salary, and then target their advertising and sales efforts accordingly. This can help the dealership to more efficiently allocate their resources and increase their sales. Similarly, an auto manufacturer can use this model to gain insights into their target market and tailor their product offerings to better meet the needs of their customers.