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Boost Your Machine Learning Skills And Be The Expert Companies Are Desperate To Hire.

Go beyond the basics and master the advanced techniques that top AI teams use. Our courses are designed to bridge the gap between theory and production, transforming you into the ML expert companies are actively searching for.

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14 Common Feature Engineering Questions

And their answers, of course!

Sole answers 14 of the most common questions students ask about feature engineering for machine learning, covering topics such as encoding, scaling, imputation, and outlier handling.

It offers clear, practical answers grounded in real-world experience to help practitioners build better, more robust machine learning pipelines.

Free PDF Download

Bestselling Courses

Forecasting with Machine Learning

Forecast single and multiple time series with machine learning models. Implement backtesting to evaluate models before deployment.

Kishan Manani

$39.99

Feature Engineering for Time Series Forecasting

Create lag, window and seasonal features, perform imputation and encoding, extract datetime variables, remove outliers, and more.

Kishan Manani

$44.99

Machine Learning Interpretability

Explain interpretable and black box models with LIME, Shap, partial dependency plots and more.

Soledad Galli

$39.99

Machine Learning Specializations

Skill-focused course bundles. Advance your career with structured learning paths.

Advanced Machine Learning

Become an expert in machine learning with our 5 course bundle.

Learn more

Forecasting Specialization

Master time series forecasting with our specialized courses.

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What our students say

Our Books

Python Feature engineering Cookbook

Feature Selection in Machine Learning

FREE Download

14 Common Feature Engineering Questions

Sole answers 14 of the most common questions students ask about feature engineering for machine learning, covering topics such as encoding, scaling, imputation, and outlier handling. It offers clear, practical answers grounded in real-world experience to help practitioners build better, more robust machine learning pipelines

Soledad Galli

FREE

7 Takes on Working with Imbalanced Data - FREE

Sole discusses three recent articles that shift the conversation around handling imbalanced datasets. These articles explore whether generating synthetic data is effective with current state-of-the-art algorithms, and examine the implications of using synthetic data on model performance and deployment.

Soledad Galli

FREE

We're the developers of Feature-engine

Feature-engine: Python Open Source Feature Engineering Library

► 300k+ downloads a month

► 2k+ stars on Github

► 60+ contributors

► Feature engineering and selection

Instructors

Soledad Galli: Data Scientist, Instructor, Open Source Developer

Soledad Galli, PhD

Lead Data Scientist

Kishan Manani, Data Scientist, Instructor

Boost Your Machine Learning Skills And Be The Expert Companies Are Desperate To Hire.

Go beyond the basics and master the advanced techniques that top AI teams use. Our courses are designed to bridge the gap between theory and production, transforming you into the ML expert companies are actively searching for.

Sign up to try the first videos of every course for free.

NEW

14 Common Feature Engineering Questions

And their answers, of course!

Bestselling Courses

Forecasting with Machine Learning

Forecast single and multiple time series with machine learning models. Implement backtesting to evaluate models before deployment.

Feature Engineering for Time Series Forecasting

Create lag, window and seasonal features, perform imputation and encoding, extract datetime variables, remove outliers, and more.

Machine Learning Interpretability

Explain interpretable and black box models with LIME, Shap, partial dependency plots and more.

Machine Learning Specializations

Advanced Machine Learning

Forecasting Specialization

What our students say

Our Books

Python Feature engineering Cookbook

Feature Selection in Machine Learning

FREE Download

14 Common Feature Engineering Questions

7 Takes on Working with Imbalanced Data - FREE

We're the developers of Feature-engine

► 300k+ downloads a month

► 2k+ stars on Github

► 60+ contributors

► Feature engineering and selection

Instructors

Soledad Galli, PhD

Lead Data Scientist

Kishan Manani, PhD

Lead Data Scientist

Dalibor Veljkovic

Lead Data Scientist

Tired of sifting through endless tutorials?

Follow us 👇

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Boost Your Machine Learning Skills And Be The Expert Companies Are Desperate To Hire.

Go beyond the basics and master the advanced techniques that top AI teams use. Our courses are designed to bridge the gap between theory and production, transforming you into the ML expert companies are actively searching for.

Sign up to try the first videos of every course for free.

NEW

14 Common Feature Engineering Questions

And their answers, of course!

Bestselling Courses

Forecasting with Machine Learning

Forecast single and multiple time series with machine learning models. Implement backtesting to evaluate models before deployment.

Feature Engineering for Time Series Forecasting

Create lag, window and seasonal features, perform imputation and encoding, extract datetime variables, remove outliers, and more.

Machine Learning Interpretability

Explain interpretable and black box models with LIME, Shap, partial dependency plots and more.

Machine Learning Specializations

Advanced Machine Learning

Forecasting Specialization

What our students say

Our Books

Python Feature engineering Cookbook

Feature Selection in Machine Learning

FREE Download

14 Common Feature Engineering Questions

7 Takes on Working with Imbalanced Data - FREE

We're the developers of Feature-engine

► 300k+ downloads a month

► 2k+ stars on Github

► 60+ contributors

► Feature engineering and selection

Instructors

Soledad Galli, PhD

Lead Data Scientist

Kishan Manani, PhD

Lead Data Scientist

Dalibor Veljkovic

Lead Data Scientist

Tired of sifting through endless tutorials?

Follow us 👇