Getting Started with Feature Engineering
Getting Started with Feature Engineering
Download this premium online course featuring high-quality video training, step-by-step lessons, practical demonstrations, and expert instruction. With Getting Started with Feature Engineering, you'll gain practical knowledge through structured learning, hands-on examples, and real-world applications. This comprehensive eLearning resource is ideal for students, professionals, freelancers, and lifelong learners looking to develop valuable skills and stay current with modern industry practices at their own pace.
Released 7/2026
By Troy Kranendonk
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 34m 57s | Size: 134.6 MB
Machine learning models can only learn from the data they're given, making feature engineering one of the most important steps in building effective predictive models.
Machine learning models can only learn from the data they're given, making feature engineering one of the most important steps in building effective predictive models. In this course, Getting Started with Feature Engineering, you'll learn how to transform raw data into meaningful features that improve machine learning performance. First, you'll explore the role of feature engineering and how it fits into the machine learning workflow. Next, you'll discover common techniques for transforming, encoding, scaling, and deriving features while applying domain knowledge to create stronger learning signals. Finally, you'll build and evaluate engineered features using Python, pandas, and scikit-learn to see how better inputs can improve model performance. When you're finished with this course, you'll have the skills and knowledge of feature engineering needed to prepare data, design effective features, and build more accurate machine learning models.
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