Technical Analysis:

While browsing through thousands of datasets on the internet, I finally came across a dataset of my interest. I sourced my dataset from Kaggle.

• Conducted comprehensive exploratory data analysis (EDA) on an Airbnb dataset to gain insights into the factors influencing listing prices.

• Developed and implemented a machine learning model using Random Forest regression to accurately predict Airbnb prices based on various features such as neighborhood, room type, and minimum nights.

• Performed feature engineering and one-hot encoding to handle categorical variables and enhance the predictive power of the model.

• Evaluated and interpreted model performance using metrics such as Root Mean Squared Error (RMSE), achieving a high level of accuracy in price predictions.