Rating 4.25 out of 5 (26 ratings in Udemy)

• In this hands-on project based course, students will learn fundamentals and actual implementation of various machine learning algorithms.
• Build regressor, classifier and clusters for real world application using online project working environment and that too without downloading any software.
• Make prediction using linear regression and optimization model coefficents using gradient descent algorithm
• To build a logistic regression classifier to predict customer purchased decision
• To classify mall customers based on k means clustering for market basket analysis. Use of ELBOW method to detect optimal k value
• To identifying the gender of a voice using SVM classifier
• Data visualization with seaborn and matplotlib library
• Model perfromance evalution using metrics like MSE, R-square error, confusion matrix, precision, recall, f1-score
• K-fold cross validation method