This is the documentation of my learning journey about classification
StrokePrediction.ipynb [Brain stroke prediction dataset]
The file contains few steps. Those are preprocessing data to generate normalization of each row and column, change the unknown values in the 'smoking_status' column with prediction results using Linear Regression, and predict stroke status using SVM SVC from sklearn.
VillainClassification.ipynb [Villains - Image Classification]
Look for the optimum Convolutional Neural Networks model step by step using Keras Tuner to get hyperparameter tuning. There are preprocessing images, splitting data, tuning model, building model, training model, and evaluating model.
BreastCancer.ipynb [Breast Cancer Dataset]
Find best features to create a Random Forest Classifier model using SelectKBest and GridSearchCV. There are preprocessing dataframe, looking for k of features selection, splitting data, building model, model fit, and evaluating model.
WaterQuality.ipynb [Water Quality]
Look for the optimum Neural Networks model using GridSearchCV to get hyperparameter tuning. There are preprocessing dataframe, finding best parameter in model, splitting data, building model, model fit, and evaluating model.