Machine Learning
3,482 learners
Data Cleaning and Preprocessing in Machine Learning
Explore essential machine learning preparation using the Titanic Dataset. Gain skills in cleaning and preprocessing historical data with Python and Pandas, readying it for ML models and accurate analytics.
Numpy
Pandas
Python
Scikit-learn
7 lessons
26 practices
4 hours
Data Cleaning and Preprocessing
Lessons and practices
Data Preprocessing with the Titanic Dataset
Adjust Filtering to Age and Fare
Debug the Titanic Dataset Loading Code
Handle Missing Data in the Titanic Dataset
Update Titanic Dataset Handling Missing Data Code
Something is missing
Data Cleaning in Titanic Dataset
Should we change the threshold?
Detecting Outliers in Titanic Dataset Using Standard Diviation
Detecting Outliers in Titanic Dataset Using IQR method
Identifying and Handling Outliers using the IQR Method
Applying MinMaxScaler to Multiple Features
Applying One-Hot Encoding to Categorical Features
Applying MinMaxScaler and One-Hot Encoding To Features
Normalize the 'age' Column in the Titanic Dataset
Standardize the 'fare' Column with NaN values in the Titanic Dataset
Normalize and Standardize 'age' and 'fare' Columns with Missing Values in the Titanic Dataset
Standardize on your own
Implement Log Transformation on 'fare’ Feature
Implement Binary Encoding on 'embark_town' Feature
Implement Log Transformation on 'fare’ Feature
Implement One-Hot Encoding on 'class' Feature
Preprocessing Train and Test data with the Titanic Dataset
Fix the Titanic Machine Learning Model
Evaluating the Titanic Machine Learning Model with a Different Metric
Understanding Feature Importance in the Titanic Logistic Regression Model
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