Mastering Machine Learning – Ep.1: Imputing Missing Values With Scikit-learn

Approximately 90% of any data scientist’s day is taken up by cleaning data. More often than not, data sets are incomplete or incorrect, forcing people to lose a significant amount of time taking corrective actions and hindering efficiency. We will look at a processing technique called Imputation that allows one to retrieve unknown data.

This session will cover:
– Simple Imputer
– Iterative Imputer
– KNN-Imputer

On top of this session, you can also sign up for the upcoming webinars of this series by clicking on the links below:

• October 14th | Mastering Machine Learning – Ep.2: Build and Run a Machine Learning Pipeline
• November 4th | Mastering Machine Learning – Ep.3: Be a Data Science Master and Commander with XGBoost
• November 18th | Mastering Machine Learning – Ep.4: Build a Sentiment Analysis Pipeline
• December 9th | Mastering Machine Learning – Ep.5: Natural Language Processes Using Amazon Sagemaker

– All registrants will receive the recording of the webinar via email