Machine Learning: Regression

Machine Learning: Regression

Machine Learning
25
Apr, 2021

COURSE DESCRIPTION

Regression is a large subset of Machine Learning problems that involves predicting a numerical value using known variables without having to personally work out relationships between those. While this course’s main focus is on constructing and utilizing an appropriate Regression model on a determined problem, you must also understand specific concepts that are universal to Machine Learning as a whole.

LEARNING OUTCOMES

  • Understand regression problems in machine learning
  • Understand and practice Simple Linear Regression and Multiple Regression
  • Understand metrics, why and how are they used for Assessing Performance
  • Understand what is Overfit, why it happens and how it impact model quality
  • Understand and practice Ridge Regression and LASSO Regression to resolve Overfit
  • Understand and practice K-Nearest Neighbor and Kernel Regression
  • Apply all learned techniques to solve real-world problems

Course Content

Time: 43 hours

Module 1 – Regression Overview  0/0

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Module 2 – Regression Algorithms  0/0

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Assignment 1: Predict ‘Visibility (km)’ attribute of the weather  0/0

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Module 3 – Regression Tuning  0/0

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Assignment 2 – Create a Regression model predicting the number of Facebook comments at a specific time and optimize the model  0/0

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Module 4 – Time Series Forecasting  0/0

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Instructor

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