Machine Learning applied to Astroinformatics
- 0.0
-
![]()
![]()
![]()
![]()
![]()
Brief Introduction
Learn to develop a machine learning project to real world problems in AstroinformaticsDescription
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.
Requirements
- 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
Knowledge
- 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
Intro to Self-Driving Cars
- 0.0
-
![]()
![]()
![]()
![]()
![]()
You will learn how to solve problems in both Python and C++ as you discover what makes self-driving cars possible. These concepts will be applied to solving self-driving car problems....
Python Machine Learning : Learn Handson™
- 4.7
-
![]()
![]()
![]()
![]()
![]()
Naive Bayes Classifier, Decision tree, PCA, kNN classifier, linear regression, logistic regression,SVM classifier Python plays a important role in the adoption of Machine Learning (ML) in the business environment....
Optimization Methods for Business Analytics
- 0.0
-
![]()
![]()
![]()
![]()
![]()
Learn how to use optimization methodologies and modeling approaches to effectively analyze data. Optimization is the search for the best and most effective solution....
Remote Sensing Image Acquisition, Analysis and Applications
- 4.5
-
![]()
![]()
![]()
![]()
![]()
Welcome to Remote Sensing Image Acquisition, Analysis and Applications, in which we explore the nature of imaging the earth's surface from space or from airborne vehicles....
