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Exploratory Data Analysis Python Tutorial Series on Vienna Hotels - Part 6 of 6 In this final video in our EDA with Python series, we delve into the process of fitting a multiple linear regression model. We’ll walk you through preparing the data, creating the model, interpreting coefficients, and more. Creating a multiple relational model is a crucial step in data analysis and will pave the way for learning to build advanced models with machine learning algorithms. 🎓 For the blog post + code snippets from this video, visit: https://bit.ly/eda-python-tutorial-ho... See the full EDA with Python Tutorial Series Part 1: • EDA with Python & Pandas (1/6): Explorator... Part 2: • EDA with Python & Pandas (2/6): Regression... Part 3: • EDA with Python & Pandas (3/6): Build a Si... Part 4: • EDA with Python & Pandas (4/6): Goodness o... Part 5: • EDA with Python & Pandas (5/6): Create Pan... Part 6: • EDA with Python & Pandas (6/6): Build a Mu... Timestamps 00:00 - Introduction to Multiple Linear Regression Fitting 00:07 - Importance of Data Cleaning and Preparation 00:16 - Setting Up the Multiple Linear Regression Model 00:30 - Defining Right-Hand Side Variables (Predictors) 00:46 - Incorporating Distance, Rating, and Star Ratings 01:05 - Creating Model Object and Fitting the Model 01:15 - Handling Missing Data in Predictors 01:50 - Imputing Missing Values Strategically 02:20 - Creating and Fitting the Model Again 03:00 - Generating Model Summary and Coefficients 03:30 - Importance of Intercept in the Model 04:00 - Interpreting R-Squared and Model Quality 04:30 - Understanding P-values and Confidence Intervals 05:00 - Writing and Interpreting the Prediction Equation 05:30 - Making Predictions and Calculating Residuals 06:00 - Using Predict Function for Efficiency 06:20 - Adding Prediction Outputs to DataFrame 06:40 - Comparing RMSE of Simple and Multiple Linear Regression 07:10 - Visualizing Predictions with Scatter Plot 07:40 - Importance of Visual Checks in Model Validation If you enjoyed this video, please like and subscribe to our channel! Leave a comment if there's a topic you'd like us to cover next. 🎓 Visit https://codingnomads.com for more resources and to learn this stuff for real. See you in next time!