Back to Course

Introduction to Machine Learning & Applications

0% Complete
0/21 Steps

Contents

Introduction To Machine Learning by Simplilearn Free

Supervised vs Unsupervised vs Reinforcement Learning Machine Learning Free

Linear Regression Analysis Linear Regression in Python Machine Learning Algorithms  Free

KNN Algorithm In Machine Learning KNN Algorithm Using Python K Nearest Neighbor Free

Types of Machine Learning Machine Learning Algorithms Machine Learning  Free

Market Prediction Using Machine Learning Machine Learning  Free

Decision Tree In Machine Learning Decision Tree Algorithm In Python Machine Learning  Free

Fake News Detection Using Machine Learning Machine Learning Projects In Python Free

Machine Learning With Python Free

Heart Disease Prediction Using Machine Learning Cardiovascular Disease Prediction Free

Top 10 Applications of Machine Learning Machine Learning Applications Free

New Lesson Free

Feature Selection In Machine Learning Feature Selection Techniques With Examples  Free

Machine Learning Interview Questions Answers Machine Learning Interview Preparation Free

Loan Approval Prediction using Machine Learning Machine Learning Projects Free

Support Vector Machine How Support Vector Machine Works SVM In Machine Learning Free

Classification In Machine Learning Machine Learning Tutorial Python Training Free

Logistic Regression Logistic Regression in Python Machine Learning Algorithms Free

AI and Machine Learning Full Course Artificial Intelligence Machine Learning Course Free

Image Classification Using CNN Deep Learning Projects Machine Learning Free

Mathematics for Machine Learning  Free

Introduction to Machine Learning & Applications KNN Algorithm In Machine Learning KNN Algorithm Using Python K Nearest Neighbor
Lesson 4 of 21
In Progress

KNN Algorithm In Machine Learning KNN Algorithm Using Python K Nearest Neighbor

1

Responses

Your email address will not be published. Required fields are marked *

  1. Caleb Obakayode January 25, 2025

    Learnt about supervised learning which is divided into 2 which are regression and classification. The learning majored in regression of which it is of 2 types; linear and multiple regression. Linear y=mx +C while for multiple we have more than one value of x.
    Learnt also about the steps to code it.

    I also need the psd file that was used for the training.

Report

Harassment or bullying behavior
Contains mature or sensitive content
Contains misleading or false information
Contains abusive or derogatory content
Contains spam, fake content or potential malware

Block Member?

Please confirm you want to block this member.

You will no longer be able to:

  • See blocked member's posts
  • Mention this member in posts
  • Invite this member to groups
  • Message this member
  • Add this member as a connection

Please note: This action will also remove this member from your connections and send a report to the site admin. Please allow a few minutes for this process to complete.

Report

You have already reported this .