Machine Learning Models in Science
About this Course
This course is aimed at anyone interested in applying machine learning techniques to scientific problems. In this course, we\'ll learn about the complete machine learning pipeline, from reading in, cleaning, and transforming data to running basic and advanced machine learning algorithms. We\'ll start with data preprocessing techniques, such as PCA and LDA. Then, we\'ll dive into the fundamental AI algorithms: SVMs and K-means clustering. Along the way, we\'ll build our mathematical and programming toolbox to prepare ourselves to work with more complicated models. Finally, we\'ll explored advanced methods such as random forests and neural networks. Throughout the way, we\'ll be using medical and astronomical datasets. In the final project, we\'ll apply our skills to compare different machine learning models in Python.Created by: LearnQuest
Related Online Courses
This Specialization will provide learners with the knowledge and skills to recognize key shifts in the industry and to have an agile perspective on how these shifts might impact their... more
Ensuring adequate nutrition is essential for infants to reach their full potential, as early-life nutritional imbalances and deficiencies may result in detrimental and often irreversible adverse... more
This Specialization provides learners with insight about operating in a transformed retail industry. You\'ll learn how to navigate the disruption in retail marketing caused by COVID-19 and to... more
In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face... more
This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business... more
Powered by
