House Price Prediction System Using Machine Learning

When individuals are in the market for a new home, they often display a more cautious approach when it comes to their budgets and overall market strategies. However, the current system for determining house prices typically lacks the essential element of predicting future market trends and potential price increases. The existing system Give the functionality for buyers, allowing them to search for houses by features or address. Machine Learning has significantly contributed to various areas such as natural language processing, product recommendations, healthcare, customer service, and automotive safety. Its widespread adoption in these fields highlights its trendiness and its potential for transformative impact. In light of this, we are incorporating Machine Learning into our project. Predicting the selling price of houses in cities such as Bengaluru remains a complex and intricate task. Numerous interrelated factors influence the property prices in these cities. Essential elements that impact the price comprise the property's size, its location, and its characteristics, including the number of rooms and bathrooms.