XGBoost Regression and feature engineering with Python | Data Analysis | Supervised learning | Price

How the feature engineering process improves model's performance? Do you want to learn the different steps of machine learning with eXtreme Gradient Boosting in regression?? Feature engineering is the process of using domain knowledge to extract features (characteristics, properties, attributes) from raw data. - Data to analyze: predicting house prices - How to do regression with Extreme Gradient Boosting? - Dealing with format date and time - Detecting outliers and dropping them - Feature engineering: create new variables - Variable importance in regression trees - Split into train and test sets - More used parameters in XGB - How to fit the model: calling the regressor - Model performance: what are MSE and R^2?? - How to improve our model?? what is next? In this amazing episode, we'll cover step by step a complete machine learning analysis for regression through the extreme gradient boosting regressor using the PRICE HOUSE EVAL with python JUPYTER NOTEBOOK. Pandas libraries for data manipulation, matplotlib for creation of graphics, sklearn for calling performances functions and XGBoost for the regressor. #The Data: https://archive.ics.uci.edu/ml/datasets/Real+estate+valuation+data+set ## Episode 1: https://youtu.be/Z2JSnrlWFfc - What is Extreme Gradient Boosting - Why to do regression? - Data to analyze: predicting house prices * null values, which variables to use - Features and characteristics : summary, select and drop - Split into train and test sets: using sklearn library * what is test size? how to control it? - More used parameters in XGB: * number of estimators, learning rate, max depth, etc. - How to fit the model: calling the regressor - Feature importance: which variables have more impact on the model? - Model performance: what are MSE and R^2?? - What is overfitting, underfitting?? ### Classification with XGB and python: https://youtu.be/ptFRggaTCXs ## Hierarchical clustering with python Video Chapter 1: https://youtu.be/m_zaJakEUm4 ## Clustering in python https://youtu.be/m_zaJakEUm4 ## clustering in R https://youtu.be/qrm8igxwHOQ Any comments or suggestions are welcome. Contact: [email protected] Mi canal de estadistica en español https://www.youtube.com/channel/UCe4UCHmQu92O03Z1fgzUXmQ # statistics and data science for beginners ##Machine learning tutorial ## Supervised learning ## statistical analysis # basic python # python from zero # artificial intelligence ## input and output, statistical analysis # Unsupervised algorithm # Partition, Hierarchical, density based clustering # data mining mineria de datos # Centroides