This code snippet includes the procedure of building a recommender system using KNN and SVD: 1. EDA for Recommender System 2. Collaborative Based Filtering Algorithms: K Nearest Neigbour vs. Singular Value Decomposition; 3. Model Evaluation: cross validation vs. train-test split; 4. Provide Top Recommendations
This notebook provides a practical guide to implement linear regression, walking through the model building lifecycle: EDA, feature engineering, model implementation and model evaluation. Please visit article "A Practical Guide to Linear Regression" for step by step guide.
Exploratory Data Analysis (EDA)
Main EDA techniques: univariate analysis, multivariate analysis, and feature engineering ... visit "Semi-Automated Exploratory Data Analysis Process in Python" for full code walk-through.
Log transformation, clipping methods, minmax scaler, standard scaler and robust scaler, visit Data Transformation and Feature Engineering in Python for full code walk-through.
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