Ensemble Learning

  • Ensemble method is a machine learning technique that combines several base models in order to produce
    one optimal predictive model. Learn the detailed maths and intutuion behind these ensemble methods.
    Solve data science problems effeciently using multiple ensemble algorthms

Created by Selva Prabhakaran

  •  20 Video Lessons

  • English

  • English captions

What you will learn

01

What is ensemble method and why is it so effecient?

02

Learn various types of ensemble methods

03

Bias Variance tradeoff using ensemble method

04

Build your first bagging model - Random Forest

05

Understand Gradient Boosting, XGBoost etc

06

Tune the hyperparameters to improve the performance

07

Interpret the complex ensemble models

08

Use all cores of laptop/pc to train models fast

Course Curriculum

Requirements

  • Courses Page1 Basics of Python
  • Courses Page1 Foundational knowledge of Data Science
  • Courses Page1 High school maths

Who should attend this course?

  • Data Science Aspirants

  • Data Science Professionals

  • Software/Data engineers interested in quantitative analysis

  • Professionals working with large datasets

  • Data analysts, economists, researchers

Instructor

Selva Prabhakaran Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I’ve put up the series of courses and projects with detailed explanations – just like an on the job experience. Hope you love it!

  • 4.5+Instructor rating

  • 200+ reviews

  • 10K+students

  • 15+ Courses

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