Machine Learning

Throughout this course, you'll explore:

• Supervised Learning: Learn how to train models using labeled data and make predictions on new, unseen data.
• Unsupervised Learning: Discover the power of learning from unlabeled data and uncover patterns and structures within it.
• Data Preprocessing: Understand the importance of preparing and cleaning data before feeding it to machine learning algorithms.
• Feature Engineering: Learn how to select and transform relevant features from your data to improve model performance.
• Regression: Dive into the world of regression algorithms and learn to predict continuous outcomes.
• Classification: Explore classification algorithms and understand how to categorize data into classes.
• Model Evaluation: Discover techniques for evaluating the performance of your machine learning models.

Throughout the course, you'll work on hands-on assignments that reinforce your understanding of each concept. These assignments will challenge you to apply what you've learned to real-world datasets and problems.

Regular quizzes will help you assess your progress and ensure you're grasping the core concepts. These quizzes are designed to be engaging and informative, providing you with instant feedback on your performance.