Data Transformations in C#: Missing Values, Normalization, OneHotEncoding | ML.Net скачать в хорошем качестве

Data Transformations in C#: Missing Values, Normalization, OneHotEncoding | ML.Net

We walk through essential data transformation techniques in C# using ML.NET. You’ll learn how to: Use Transformers to build repeatable data-processing workflows Replace missing values to keep your dataset consistent Drop unnecessary columns for cleaner modeling Apply Min-Max Normalization to scale numerical features Perform One-Hot Encoding for categorical variables Concatenate multiple columns into a single feature vector These preprocessing steps are the foundation of building high-quality ML models in ML.NET, ensuring your data is clean, structured, and ready for training. #MLNet #CSharp #MachineLearning #DataPreprocessing #FeatureEngineering #OneHotEncoding #Normalization #AIForDevelopers