From the course: Applied Machine Learning: Feature Engineering
Applied ML: Feature engineering - Python Tutorial
From the course: Applied Machine Learning: Feature Engineering
Applied ML: Feature engineering
- If you have a bunch of data and are wondering how to extract value from it, perhaps you're aiming to forecast future trends or make informed decisions based on your data. In this course, we'll guide you through the nuances of feature engineering techniques for numeric data, such as imputation, bending, log transformations, scaling. We won't stop there. We'll also cover methods for other column types as well. We'll look at one hot encoding, mean targeting coding, principle component analysis, feature aggregation, and even text processing techniques like TF-IDF and embeddings. I'm Matt Harrison, your navigator on this journey. With years of experience as a corporate trainer and the author of multiple books on Python and data science, I've guided thousands of learners like you to unlock the power of their data. Now it's your turn.
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