Introduction

Welcome to my first machine learning project! The primary objective of this project is to predict prices using machine learning techniques. I have conducted a basic Exploratory Data Analysis (EDA) on the dataset and implemented three different models. The goal is to compare these models and determine the best-performing one for price prediction.

Exploratory Data Analysis (EDA)

I began by thoroughly exploring the dataset to gain a deeper understanding of its characteristics. This involved analyzing data distributions, identifying outliers, handling missing values, and visualizing key trends. EDA played a crucial role in informing subsequent modeling decisions and ensuring a comprehensive understanding of the data.

Model Comparison

For this project, I implemented three machine learning models: LinearRegression,DecisionTreeRegressor and RandomForestRegressor. Each model was chosen based on its suitability for the task and its potential to capture the underlying patterns in the data. I trained and evaluated each model, comparing their performance metrics and assessing how well they predicted prices.

Results

After a rigorous comparison, RandomForestRegressor emerged as the most accurate in predicting prices. The performance metrics, such as After Cross-Validation calculated 200 rmse and then found out the mean and std of these rmse's, indicate its superior capability in capturing the underlying patterns in the dataset. This model is selected as the final choice for price prediction in this project.

Future Steps

As my first machine learning project, there is always room for improvement. In the future, I plan to explore additional feature engineering techniques, experiment with more advanced models, and further optimize the selected model to enhance its predictive accuracy.

Conclusion

In conclusion, this project marks my initiation into the field of machine learning. Through EDA and model comparison, I have gained valuable insights into the dataset and identified a robust model for predicting prices. This experience serves as a foundation for future projects and continuous learning in the exciting realm of machine learning.

Acknowledgement

The project is for educational purposes and was created as part of @Prodigy_Infotech Internship

Feel free to explore, modify, or expand upon this project!

If you have any questions, suggestions, or feedback, please feel free to email me at [email protected]