05 - Predict House Prices with Multivariable Linear Regression

05 - Predict House Prices with Multivariable Linear Regression: 00:00:00 __ 001 Defining the Problem 00:04:46 __ 002 Gathering the Boston House Price Data 00:11:46 __ 003 Clean and Explore the Data (Part 1) Understand the Nature of the Dataset 00:24:50 __ 004 Clean and Explore the Data (Part 2) Find Missing Values 00:42:09 __ 005 Visualising Data (Part 1) Historams Distributions & Outliers 00:54:48 __ 006 Visualising Data (Part 2) Seaborn and Probability Density Functions 01:03:19 __ 007 Working with Index Data Pandas Series and Dummy Variables 01:21:24 __ 008 Understanding Descriptive Statistics the Mean vs the Median 01:31:37 __ 009 Introduction to Correlation Understanding Strength & Direction 01:38:18 __ 010 Calculating Correlations and the Problem posed by Multicollinearity 01:52:48 __ 011 Visualising Correlations with a Heatmap 02:14:25 __ 012 Techniques to Style Scatter Plots 02:31:46 __ 014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques 02:55:46 __ 015 Understanding Multivariable Regression 03:01:53 __ 016 How to Shuffle and Split Training & Testing Data 03:12:14 __ 017 Running a Multivariable Regression 03:20:56 __ 018 How to Calculate the Model Fit with R-Squared 03:25:16 __ 019 Introduction to Model Evaluation 03:27:56 __ 020 Improving the Model by Transforming the Data 03:48:18 __ 021 How to Interpret Coefficients using p-Values and Statistical Significance 03:57:27 __ 022 Understanding VIF & Testing for Multicollinearity 04:19:17 __ 023 Model Simplification & Baysian Information Criterion 04:38:52 __ 024 How to Analyse and Plot Regression Residuals 04:49:51 __ 025 Residual Analysis (Part 1) Predicted vs Actual Values 05:06:21 __ 026 Residual Analysis (Part 2) Graphing and Comparing Regression Residuals 05:26:13 __ 027 Making Predictions (Part 1) MSE & R-Squared 05:45:43 __ 028 Making Predictions (Part 2) Standard Deviation RMSE and Prediction Intervals 05:58:32 __ 029 Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays 06:16:56 __ 030 Python - Conditional Statements - Build a Valuation Tool (Part 2) 06:36:47 __ 031 Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module