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 equips you with foundational knowledge of algorithms and problem-solving in JavaScript, focusing on beginner algorithm challenges, Binary Search, and Merge Sort. You will... more
Unlock the transformative power of AI in data analysis with this Gen AI for Data Analysis Professional Certificate. Designed for both seasoned data professionals and aspiring analysts, this... more
\"Everyday Excel, Part 3 (Projects)\" is a continuation of \"Everyday Excel, Parts 1 and 2\". It is a capstone, projects-based course in which you will apply what you\'ve learned previously to more... more
In this course, you will: - Explore the applications of GANs and examine them wrt data augmentation, privacy, and anonymity - Leverage the image-to-image translation framework and identify... more
This course helps to build the foundational material to use mathematics as a tool to model, understand, and interpret the world around us. This is done through studying functions, their properties,... more

CONTINUE SEARCH

FOLLOW COLLEGE PARENT CENTRAL