Machine Learning – 1 (Prediction Algorithms)

Faruk Celikkanat
Last Update April 15, 2021

About This Course

This training aims to ensure that participants who want to improve themselves in machine learning can learn this subject from the ground up.

In this training, you will learn and apply the necessary statistics and machine learning techniques to produce solutions to prediction problems encountered in real life.

The training process is based on the participants’ learning by actively developing projects.

Training subjects for this course:

• Simple Linear Regression
• Multiple Linear Regression
• Regularized Linear Regression (Ridge, Lasso, Elastic Net)
• Polinomial Regression
• Support Vector Regression
• Decision Tree Regression
• Ekstra Tree Regression
• Random Forest Regression
• Ensemble Methods (Bagging, Boosting, Stacking)
• Comparison and Evaluation of Methods

Learning Objectives

You will be able to make statistical analysis to prediction problems encountered in real life
You will learn theoretical and applied estimation algorithms
You will be able to develop prediction algorithms in the python programming language

Requirements

  • Basic python knowledge

Target Audience

  • Those who want to specialize in machine learning
  • Those who want to create the foundations of artificial intelligence
  • Those who want to start or continue their career in machine learning
  • Those who want to apply machine learning in business life

Zoom Live Meetings

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Your Instructors

Faruk Celikkanat

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Free
Level
All Levels
Duration 1 hour
Language
English

Enrolment validity: Lifetime

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