Machine Learning applied to Astroinformatics

Duration: 1h 58m | Video: .MP4 1280×720, 30 fps(r) | Audio: AAC, 44100 Hz, 2ch | Size: 1.19 GB

Genre: eLearning | Language: English

Learn to develop a machine learning project to real world problems in 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

Requirements
Basic knowledge of Python is required in order to understand the analysis (but I explained you all the code we are developing)
No previous knowledge in Machine Learning is required
No previous knowledge in Astroinformatics is required

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

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