Supervised ML Algorithms

  • Enjoy learning the intuition, concept and underlying math behind Supervised Learning algorithms
    with complete clarity and have all your doubts answered. You will learn several nuances and special
    cases, gain mastery to confidently crack Interviews..

Created by Selva Prabhakaran

  • 58 Video Lessons

  • English

  • English captions

What you will learn

01

What is supervised learning and different algorithms under it?

02

In depth understanding of KNN, Naive Bayes, SVM, Decision Tree etc.

03

When to use which type of algorithm

04

How a problem can be solved using various algorithms

05

How to tune the hyperparameters

06

Evaluate the model using various evaluation metrices

07

Implement the algorithms in a project and solve it end to end

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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