![]() ![]() One powerful way to predict the future is to carefully review the past. Sometimes we are ready and waiting and yet we miss it when Opportunity rings our door bell. Being connected has a built-in advantage. We miss opportunities because we are blinkered and out of the loop. Upgrading your skills is one way to invite Opportunity to knock. ![]() Opportunity might be filling the demand for certain skills, but you have decided to stick to what you know. Opportunity might not be knocking on your door because she is busy elsewhere. ![]() Digging elsewhere might not be the solution. The treasure you seek might just be a few feet deeper. One success strategy is to dig deeper instead of wider. We miss opportunities by giving up too early. When Opportunity knocks make sure you are at the right address. Who among us have never rued a missed opportunity? GitHub Page link for the project : #dataanalysis #datascience #DelhiHousePricePrediction #HousePricePrediction #machinelearning #DataGeek #DataEnthusiast #ConnectAndLearn #DataScienceCommunity #kaggle #datascientists #like #share #github #githubpages #data #dataanalytics #AI #ML #website #delhi By marrying data analysis and machine learning, the project not only addresses the need for precise price predictions in Delhi's real estate market but also provides actionable insights for prospective buyers and sellers alike. The project employs advanced regression models, including Decision Tree Regressor and Random Forest Regressor, achieving a remarkable accuracy rate of 84.98% with the latter. Moreover, the preference for new builder floor properties signifies a demand for customization among buyers. It has been discovered that house prices are intricately influenced by variables such as area, bedroom count, and specific localities like Punjabi Bagh and Vasant Kunj. Through extensive exploratory data analysis (EDA), the project has unveiled noteworthy insights. The project utilizes a robust dataset sourced from Kaggle, encompassing essential factors like house area, bedroom count, and locality. The "Delhi House Price Prediction" project is a data science endeavor focused on creating an accurate predictive model for estimating house prices across various localities in Delhi. Models Used - Decision Tree Regressor and Random Forest Regressor ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |