The Complete Machine Learning Course with Python

After completing The Complete Machine Learning Course with Python online course, learners will understand about kinds of regressions, classification, and other metrics like R-squared, MSE, accuracy, confusion, matrix, perversion, recall, and using them at right time, machine learning tools to solve issues. They will learn how bagging, boosting, or stacking can combine numerous models, to pick the correct model and forecast model performance with unseen data and utilise train/test, K-fold, and Stratified K-fold cross-validation, use unsupervised machine learning algorithms like hierarchical clustering and k-means clustering to analyse data. Candidates will be skilled to use SVM for handwriting recognition and classifying problems, using decision trees to forecast employee attrition, and communicating visually and effectively with Matplotlib and Seaborn.