Enroll Course: https://www.udemy.com/course/ml-feature-engineering/
Are you diving into the world of machine learning and finding that your models aren’t performing as well as you’d hoped? Often, the secret sauce isn’t in complex algorithms, but in the art of Feature Engineering. This Udemy course, “【初心者向け】機械学習モデル構築で重要な特徴量エンジニアリングのテクニックをPythonを使って学んでいこう！” (Learn Key Feature Engineering Techniques for Machine Learning Model Building with Python for Beginners!), is an absolute game-changer for anyone looking to elevate their machine learning skills.
This course brilliantly breaks down one of the most crucial steps in machine learning: Feature Engineering. Designed with beginners in mind, it meticulously explains various essential techniques. You’ll learn how to handle outliers, impute missing values, and tackle imbalanced datasets – all fundamental skills for robust model building. The course also delves into creating new features by combining existing ones and explores different encoding methods for categorical variables like One-Hot Encoding and Label Encoding. Date data processing, including cyclical encoding, is covered, as is the creation of new features using cluster analysis. Furthermore, you’ll master numerical variable scaling techniques such as log transformation.
The real magic happens when you get to apply these concepts. The course uses the classic Titanic dataset from Kaggle, a popular starting point for data analysis competitions. Through hands-on practice, you’ll experience firsthand how to engineer features to improve model accuracy. It’s the perfect course for those who feel stuck with their model performance or want to gain more practical, real-world knowledge.
If you’re aiming to become a more valuable asset in the job market, mastering feature engineering is a must. This course provides a clear, step-by-step path to achieving that mastery. Highly recommended for aspiring data scientists and machine learning engineers!
Enroll Course: https://www.udemy.com/course/ml-feature-engineering/