House price prediction

[SayantikaLaskar]

Predicting house prices using machine learning involves several challenges. Ensuring high accuracy is crucial as incorrect predictions can significantly impact buyers and sellers. House prices depend on many factors such as location, size, age, and condition of the property, making feature selection and data preprocessing vital. Obtaining a comprehensive and representative dataset is essential to avoid bias and poor model performance. Choosing the right machine learning algorithm, whether linear regression, decision trees, or neural networks, requires balancing complexity, interpretability, and computational resources. The model must generalize well to new, unseen data to be useful in real-world applications. Regular updates and maintenance of the model are necessary to incorporate new data and market trends. Addressing these issues is key to developing an effective house price prediction system that provides reliable and valuable insights.

[github-actions[bot]]

Thank you for creating this issue! 🎉 We'll look into it as soon as possible. In the meantime, please make sure to provide all the necessary details and context. If you have any questions reach out to LinkedIn. Your contributions are highly appreciated! 😊

You can also check our CONTRIBUTING.md for guidelines on contributing to this project.

[pavitraag]

Please assign this to me under gssoc 24

[sonali9564]

@sanjay-kv Please assign this issue to me under GSSoC'24.

[Akanksha4554]

@sanjay-kv Please assign this issue to me under GSSoc'24.