Machine Learning applied to Astroinformatics
What you'll learn
- How to apply machine learning techniques to real world problems in the area of Astroinformatics
- Learn to implement useful and popular machine learning algorithms
- Learn what Astroinformatics is
- Learn about supervised and unsupervised machine learning approaches
- Learn to train a machine learning model
- Learn how to apply machine learning to light curves
- Learn how a real data analysis project is developed
- Learn how to work with data files and load for data analysis
- Learn how to use free python libraries for machine learning
- Learn how to use jupyter notebook as a tool to develop a machine learning project
- Get valuable insights from data analysis and build a report
Description
In this course, you are going to learn how to develop a machine learning project to solve real-world problems that you can find in the Astroinformatics area.
You will learn the more practical and useful algorithms that can help you to do predictions and work with big data.
If you are not familiar with machine learning and Astroinformatics, don't worry, because in this course, you will learn the necessary to understand these areas, so easily you will apply these techniques to real-world projects.
And as we know, the best way to learn is making, so we will develop a project using python, in which we are going to analyze simulated data of a real-world telescope and we are going to develop different machine learning models in order to classify different astronomical objects into different astronomical classes.
So, get started in machine learning with this amazing course and start to learn a little bit about how machine learning can improve the astroinformatics world.
Who this course is for:
- Anyone who wants to learn about Machine Learning and its applications to Astroinformatics area
- Anyone who wants to learn how to build a real world machine learning project
Course content
- Preview01:44
- 01:54Astronomical objects and their measurements
- 02:32Electromagnetic emissions
- 02:30Types of Astronomical objects: Variables and Transients
Instructor
![Leo Bravo](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.0 Instructor Rating
- 82 Reviews
- 4,976 Students
- 6 Courses
I am a Chemical Engineer and Master in Data Science. Actually I am working with deep learning applied to Astronomical data! It's crazy but it's fun too.
I love to teach and I always have been doing classes. I started doing classes at University (for a master course) and then, doing classes in other universities and private classes.
I also love to build things, especially digital things, so for that reason, I love to program and build software (mobiles, web and now, deploy machine learning models).
I hope you can enjoy my courses, and if you have any doubt, you can contact me.