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Rentonomics: A Machine Learning Approach to House Rent Predication

B. Manaswini, A. Sneha, M. Bharathi, T. Aditya Sai Srinivas

Abstract


This paper explores the dynamic factors influencing house rent, emphasizing the pivotal role of data and Machine Learning (ML) in shaping housing options based on individual budgets. Delving into the application of ML techniques, the discussion centers on guiding readers through the process of predicting house rent using Python. By providing insights into the intersection of real estate and technology, the article aims to equip readers with the knowledge and tools necessary to navigate the realm of ML-driven house rent predictions.


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References


https://www.kaggle.com/code/rkb0023/exploratory-data-analysis-house-rent-prediction

https://www.kaggle.com/code/rkb0023/model-building-house-rent-prediction

https://www.analyticsvidhya.com/blog/2023/06/a-deep-dive-into-lstm-neural-network-based-house-rent-prediction/

https://medium.com/mlearning-ai/house-rent-prediction-with-machine-learning-2960d753e3ca

https://thecleverprogrammer.com/2022/08/15/house-rent-prediction-with-machine-learning/


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