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IDEs for Machine Learning Best IDEs for Machine Learning Great Learning

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Lessons List | 17 Lesson
Supervised Machine Learning Tutorial Logistic Regression Naive Bayes Classifier
02:58:06

Supervised Machine Learning Tutorial Logistic Regression Naive Bayes Classifier
Multi layer Perceptron in Neural Network Machine Learning Tutorial What is Multilayer Perceptron
02:07:05

Multi layer Perceptron in Neural Network Machine Learning Tutorial What is Multilayer Perceptron
Linear Regression in Machine Learning what is linear regression Machine Learning Tutorial
02:14:48

Linear Regression in Machine Learning what is linear regression Machine Learning Tutorial
Python Machine Learning for Beginners Machine Learning Python Machine Learning with Python 2023
02:29:03

Python Machine Learning for Beginners Machine Learning Python Machine Learning with Python 2023
Linear Discriminant Analysis LDA Discriminant Analysis Tutorial Machine Learning Tutorial
01:29:40

Linear Discriminant Analysis LDA Discriminant Analysis Tutorial Machine Learning Tutorial
IDEs for Machine Learning Best IDEs for Machine Learning Great Learning
02:06:06

IDEs for Machine Learning Best IDEs for Machine Learning Great Learning
Classification Algorithm Tutorial Machine Learning Tutorial Great Learning
09:40:03

Classification Algorithm Tutorial Machine Learning Tutorial Great Learning
Python Libraries for Machine Learning Scipy NumPy Pandas Matplotlib Great Learning
04:24:32

Python Libraries for Machine Learning Scipy NumPy Pandas Matplotlib Great Learning
Supervised Learning Projects Tutorial Machine Learning Tutorial Great Learning
02:58:39

Supervised Learning Projects Tutorial Machine Learning Tutorial Great Learning
Become a Machine Learning Engineer Roadmap to Machine Learning Engineer Great Learning
00:05:07

Become a Machine Learning Engineer Roadmap to Machine Learning Engineer Great Learning
Preparing Data for Machine Learning Models Data Balancing Techniques Great Learning
01:01:46

Preparing Data for Machine Learning Models Data Balancing Techniques Great Learning
ML Model Deployment using R Shiny Machine Learning Tutorial Great Learning
00:53:41

ML Model Deployment using R Shiny Machine Learning Tutorial Great Learning
Application of Classification Algorithms Machine Learning Tutorial Great Learning
01:24:15

Application of Classification Algorithms Machine Learning Tutorial Great Learning
Machine Translation Statistical Machine Translation Model Great Learning
01:23:07

Machine Translation Statistical Machine Translation Model Great Learning
Bias Variance Tradeoff Bias and Variance in Machine learning Great Learning
00:28:40

Bias Variance Tradeoff Bias and Variance in Machine learning Great Learning
Boosting Boosting Machine Learning Tutorial Bagging vs Boosting Great Learning
01:43:47

Boosting Boosting Machine Learning Tutorial Bagging vs Boosting Great Learning
Scikit Learn Machine Learning With Scikit Learn SK learn Great Learning
01:06:35

Scikit Learn Machine Learning With Scikit Learn SK learn Great Learning

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Punyashree Punyashree 

Nice
2026-05-21

Keerthana 

Very helpful
2026-05-11

Roopa Shri 

Good
2026-05-10

Raghu Raghu n 

It was soo helpfull to find the entire learning this website proves us tht evn with mobile phone we gain lots of knowledge
2026-05-10

Teju Teju 

Use full classes
2026-05-09

Shwetha S 

👍
2026-05-01

Rukmini m 

👍
2026-05-01

Bhagyalakshmi N 

Good
2026-04-30

Kunal Chand 

course is really helpful
2026-04-13

Mayank Bargali 

the course was good
2026-04-12

Nirmal Singh 

good
2026-04-12

megha mehta 

good
2026-04-12


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Course Description

Python for Machine Learning course, in this course we will learn about using Python for machine learning applications. Covering essential libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn, students will gain hands-on experience in data preprocessing, visualization, and building predictive models. Through practical exercises and projects, participants will develop proficiency in leveraging Python's ecosystem for various machine learning tasks, from data cleaning to model evaluation and deployment.
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