通过实际案例研究掌握机器学习
- 1 - Linear Regression using House Rent Prediction
- 1 - 1 - Introduction to Linear Regression.mp4
- 2 - 2 - Linear Regression.mov
- 3 - 3 - Import Data.mov
- 4 - 4 -Outlier Function.mov
- 5 - 5 - Visualization.mov
- 6 - 6 - Encode Data.mov
- 7 - 7 - Linear Model.mov
- 8 - 8 - Cross Validation and RMSE.mov
- 9 - 9 - Plot Predictions.mov
- 10 - 10 - Tabulate Results.mov
- 2 - Multicollinearity using Car Dataset
- 1 - 1 - Introduction.mp4
- 2 - 2 - Linear Regression Data.mov
- 3 - 3 - EDA Part 1.mov
- 4 - 4 - EDA Part 2.mov
- 5 - 5 - EDA Part 3.mov
- 6 - 6 - Variance Inflation Factor.mov
- 7 - 7 - Predictions.mov
- 3 - Logistic Regression using Credit Card Fraud Classification
- 1 - 1 - Introduction.mov
- 2 - 2 - Logistic Regression.mp4
- 3 - 3 - EDA Part 1.mov
- 3 - 4 - EDA Part 2.mov
- 4 - 5 - Data Scaling Part 1.mov
- 5 - 6 - Data Scaling Part 2.mov
- 6 - 7 - Outlier Visualization.mov
- 7 - 8 - Predictions.mov
- 8 - 9 - Finding Best Parameters.mov
- 4 - SVC using Bank Customer Retirement Classification
- 1 - 1 - SVC.mov
- 5 - Regularization using Sales Price Dataset
- 1 - 1 - Regularization Part 1.mov
- 2 - 2 - Regularization Part 2.mov
- 6 - Decision Tree
- 1 - 1 - EDA.mov
- 2 - 2 - Model Predictions.mov
- 7 - Random Forest using Housing Price Dataset
- 1 - 1 - Introduction to Random Forest.mp4
- 2 - 2 - Overview.mov
- 3 - 3 - Import Dataset.mov
- 4 - 4 - Metrics.mov
- 5 - 5 - Working of Random Forest.mov
- 6 - 6 - Linear Regression Modeling.mov
- 7 - 7 - Linear Regression Predictions.mov
- 8 - 8 - Random Forest Modeling.mov
- 9 - 9 - Random Forest Predictions.mov
- 10 - 10 - Comparison.mov
- 8 - PCA using Housing Price Prediction
- 1 - 1 - Part 1.mov
- 2 - 2 - Part 2.mov
- 9 - K-Means using Social Media and Customer Segmentation
- 1 - 1 - KMeans using Social Media Dataset Part 1.mov
- 2 - 2 - KMeans using Social Media Dataset Part 2.mov
- 3 - 3 - KMeans using Mall Customer Segmentation Part 1.mov
- 4 - 4 - KMeans using Mall Customer Segmentation Part 2.mov
- 10 - Naive Bayes using Fraud Classification
- 1 - 1 - Introduction.mov
- 2 - 2 - Load Dataset.mov
- 2 - 3 - EDA.mov
- 3 - 4 - Modeling.mov
- 4 - 5 - Results.mov
- 11 - AdaBoost using Housing Price Prediction
- 1 - 1 - Load Dataset.mov
- 2 - 2 - EDA.mov
- 3 - 3 - Modeling and Prediction.mov
- 12 - ARIMA
- 1 - 1 - Introduction Part 1.mov
- 2 - 2 - Introduction Part 2.mov
- 3 - 3 - Stationarity Checks.mov
- 4 - 4 - Seasonal Decomposition Part 1.mov
- 5 - 5 - Seasonal Decomposition Part 2.mov
- 6 - 6 - Modeling and Prediction.mov
- 13 - XGB using Stock Dataset
- 1 - 1 - Introduction.mov
- 2 - 2 - EDA.mov
- 3 - 3 - Data Preparation.mov
- 4 - 4 - Modeling.mov
- 5 - 5 - Backtesting.mov
- 6 - 6 - Results.mov