Supervised Machine Learning Algorithms

Name: Supervised Machine Learning Algorithms
Price: 299.00 USD

6 Lesson

6 Hours

Add to Wishlist

Supervised Machine Learning Algorithms Training is designed to help you understand the fundamental algorithms used to build predictive machine learning models. In this training, you will learn how supervised learning works using labeled datasets and explore common algorithms such as linear regression, logistic regression, decision trees, and k-nearest neighbors. By the end of the course, you will understand how these algorithms are used to solve regression problems in machine learning. This course is suitable for beginners, students, and professionals who want to start learning the core supervised learning techniques used in machine learning and data science.

Enroll Now

Overview

Supervised machine learning is used to build predictive models using labeled data. In this course, you will learn from data professionals with over 18 years of experience through live classes.

Prerequisites:

Basic understanding of Python programming
Familiarity with datasets and basic data concepts
Basic knowledge of statistics and probability
Interest in machine learning and data analysis

What Will You Learn:

Fundamentals of supervised machine learning
Understanding labeled datasets
Linear regression for prediction
Logistic regression for classification
Decision trees and random forests
K-nearest neighbors (KNN)
Support vector machines (SVM)
Model evaluation techniques

Key Features

1 On 1 Training Option Available
24 X 7 Lifetime Support & Access
Small Batches Upto 10 Participants
Experienced & Professional Trainers

Course Curriculum

Lesson 1 - Introduction to Supervised Machine Learning

1. Supervised learning concepts and workflow

2. Labeled datasets and target variables

3. Regression vs classification problems

Lesson 2 - Linear Regression

1. Simple and multiple linear regression

2. Model training and prediction

3. Evaluating regression model performance

Lesson 3 - Logistic Regression for Classification

1. Binary classification concepts

2. Logistic regression model training

3. Interpreting classification results

Lesson 4 - Decision Trees and Random Forests

1. Decision tree structure and splitting criteria

2. Preventing overfitting in decision trees

3. Random forest ensemble method

Lesson 5 - K-Nearest Neighbors (KNN)

1. KNN algorithm concept

2. Distance metrics in KNN

3. Choosing optimal K values

Lesson 6 - Support Vector Machines (SVM)

1. SVM classification concepts

2. Hyperplane and margin concepts

3. Kernel functions in SVM

Talk To Us

We are happy to help you

1-800-7430-173 (US Toll Free)

+91 7240740740 (India)

Drop Us a Query

Fields marked * are mandatory

Name

Phone Number

Comments

Request For Live Demo Class

Course Fees

Online Class Room Program

US $ 299.00

100% Money Back Guarantee

Duration : 6 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 15 Jun 2026
Weekday Batch 15 Jun 2026
Weekend Batch 20 Jun 2026

Corporate Training

Customized Training Delivery Model
Flexible Training Schedule Options
Industry Experienced Trainers
24x7 Support

Trusted By Top Companies Worldwide

Want to know Today's Offer

Certification

After completing the Supervised Machine Learning Algorithms Training, you will receive an igmGuru Course Completion Certificate. This certification confirms your understanding of key supervised learning algorithms such as linear regression, logistic regression, decision trees, and k-nearest neighbors used in machine learning projects.

Reviews

Login

Email ID*

Password*

Forgot Password?

Supervised Machine Learning Algorithms