Overview

Machine learning is the foundation for the technologies that power everything from spam filters to self-driving cars. In this introductory course, students will learn the basics of machine learning, from classical ML to neural networks. Students will also learn how to apply machine learning to real-world problems.

Throughout the course, students will delve into a wide range of machine learning algorithms. They will learn how to preprocess and transform data, select relevant features, handle missing values, and perform model evaluation and validation. Practical exercises and hands-on projects will provide ample opportunities for participants to apply their knowledge and develop their own machine learning models.

By the end of this course, students will be equipped with the necessary skills to embark on their own machine learning projects and make meaningful contributions in this rapidly evolving field. They will understand where they should pay attention when building ML systems.

This abstract was created by LLM (large language model). Want to know more? Join this course.