When signaficant amount of data are missing, what can we do? Impute the missing data with mean or median? Actually, Scikit-Learn provides two powerful imputers, KNNImputer and IterativeImputer, which can do this work effectively.

A loja de moda InStyle é uma grande loja de roupas, mas enfrenta desafios significativos em relação à experiência do cliente. Em vista disso, a InStyle montou uma equipe com a tarefa de treinar um algoritmo para classificar os clientes em satisfeitos e insatiseitos a fim de agir rápido e reverter a situação.

Simulation study for evaluating different imputation methods

while we load the dataset we get some missing values from dataset. so to replace the missing values we use a technique in Machine Learning called Imputation. Imputation --- 1. SimpleImputer 2.KNNImputer

House prices dataset exploration and prediction. Workflow includes useful examples of Tensorflow pipelines including k-Nearest Neighbors imputer, Decision Tree Regression and XGBoost Regression

We build a model to predict the value of used cars, while also considering speed and quality of the prediction.

Data Preprocessing - PCA

Разработка алгоритма привлечения новых клиентов банка