What will you learn in this course?

Develop and implement key machine learning algorithms for classification, regression, and clustering tasks using real-world datasets
Analyze and select appropriate algorithms based on data characteristics and project goals in machine learning applications
Optimize machine learning models through parameter tuning, cross-validation, and feature engineering techniques

Evaluate model performance using metrics like accuracy, precision, recall, and F1 score in practical scenarios
Apply machine learning algorithms to solve problems in various industries such as healthcare, finance, and marketing
Integrate machine learning models into software applications for real-time data analysis and decision-making

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Lessons | 6

00:10:32

Linear Regression Algorithm Tutorial | Linear Regression Explained

00:11:41

Logistic Regression Algorithm Tutorial | Logistic Regression Explained

00:13:15

Support Vector Machine SVM Algorithm Tutorial | Support Vector Machine Explained

00:14:42

Random Forest Algorithm Tutorial | Random Forest Explained

00:14:59

K means Clustering Algorithm tutorial

00:13:43

KNN Algorithm tutorial

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Machine learning algorithms types

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4.5

96 Reviews

Kaviya Sri

Great

2026-10-29

Abbagouni Nandini goud

This is helpful

2026-10-25

Shardul Shashikant Tajane

Amazing

2026-10-17

HARJOT SINGH FLORA

Good

2026-10-15

ANJALI CHALEKAR

good

2026-10-15

SIDHAN MAHULKAR

No

2026-10-15

NUPUR PATIL

the course was good

2026-10-14

Arpita S Patil

Nice

2026-10-14

ARYAN RASAM

Nice

2026-10-14

Sweety Ghadge

good

2026-10-13

Amruta Patil

great

2026-10-03

akshata walke

hi

2026-10-01

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