Welcome to the final lecture of our Python for Data Science course! 🎉 In this comprehensive session, we wrap up our capstone project by comparing #linearregression and #randomforestregression models to predict the price of pre-owned cars.
In our previous lecture, we covered:
- Handling missing values and removing duplicates.
- Creating a new variable to accurately determine the age of each car.
- Analyzing the distributions of key numerical variables.
- Understanding correlations between these variables.
Today, we delve into:
- Building and evaluating linear regression and random forest regression models.
- Comparing the performance of models using data with omitted missing values and imputed missing values.
- Using metrics like RMSE and R-squared to assess model accuracy.
- Highlighting the superior performance of the random forest model.
Join us as we explore how these models perform under different data conditions and draw conclusions from our findings. This lecture equips you with practical skills in regression modeling, essential for real-world data science challenges. Don't miss out on these valuable insights!
🔍 Keywords: Data Science, Python Programming, Machine Learning, Regression Models, Linear Regression, Random Forest, Data Cleaning, Data Imputation, Predictive Modeling, Capstone Project
Join our active user community and benefit from Python's open-source nature, continuous improvement, and scalability. By the end of the course, you'll be well-equipped to build real-life data science applications and take on more complex challenges.
Don't miss out on this opportunity to boost your data science skills and enhance your career prospects.
Subscribe now and embark on your data science journey with Python!
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Link to Data: github.com/theaiacademy1/Python-for-data-science/blob/main/Usedcars.csv
Link to Code File: github.com/theaiacademy1/Python-for-data-science/blob/main/Regression%20Model-checkpoint.ipynb
Link to Code file: github.com/theaiacademy1/Python-for-data-science/blob/main/Regression%20Model-checkpoint.ipynb
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Data Science, Machine Learning, Python Programming, Data Analysis, Regression Analysis, Predictive Modeling, Pre-Owned Cars, Price Prediction, Data Cleaning, Outliers, Data Visualization, Python Tutorial, Data Science Case Study, Ecommerce Analytics
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#DataScience #PythonProgramming #MachineLearning #RegressionModels #LinearRegression #RandomForest #DataCleaning #PredictiveModeling #CapstoneProject