Standard Scaler in Machine Learning
In this tutorial, you will learn how to standardize or normalize the feature values in Machine learning with standardscaler method.
I covered the following:
Introduction to Logistic Regression
Data Preparation for Logistic Regression
Encoding categorical variables using LabelEncoder for scikit-learn
Standardize and normalize the data points using StandardScaler
Split the data into training and testing sets using train_test_split
Train the model using the LogisticRegression class scikit-learn library
Predict the test dataset
Evaluate the model performance using precision, recall, f1-score from sckit-learn metrics module
Save and Deploy the model using the Pickle library
Test the model using the new test dataset
Learn about Pickle here: • Pickle Tutorial - How to save data in...
Learn more about Linear Regression with a real-world example: • Machine Learning Tutorials
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