Mwenda Raini shares on how to approach a prediction problem with the right data scientist mindset. Topics covered include data cleaning & formatting, summary statistics, how to handle missing values, exploratory data analysis (EDA), underfitting, overfitting, multicollinearity, normalization, feature engineering and feature selection.
Find the dataset and notebook used for this session on https://github.com/MwendaMugendi/zind…
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