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Machine Learning with scikit learn

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Track :

Programming

Lessons no : 10

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What will you learn in this course?
  • Implement data preprocessing techniques using scikit-learn for improved model accuracy and reliability
  • Apply supervised and unsupervised machine learning algorithms with scikit-learn for real-world data analysis
  • Evaluate model performance using scikit-learn metrics such as accuracy, precision, recall, and F1 score
  • Develop predictive models for classification and regression tasks with scikit-learn tools
  • Utilize scikit-learn pipelines for streamlined data transformation and model training workflows
  • Optimize machine learning models through hyperparameter tuning and cross-validation techniques

How to Get The Certificate

  • You must have an account Register
  • Watch All Lessons
  • Watch at least 50% of Lesson Duration
  • you can follow your course progress From Your Profile
  • You can Register With Any Course For Free
  • The Certificate is free !
Lessons | 10

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4.3
52 Reviews
DEEKSHA JAIN SR 

GOOD
2025-12-02

Nandani Chaudhary 

Great
2025-12-01

Anshu Man 

GOOD
2025-11-25

Farheen Nawaz 

Nice
2025-11-23

pujitha d 

Good
2025-11-19

coderworld class 

good experience
2025-11-18

sampath yadav 

good
2025-11-13

Aditya Singh 

Aditya Singh
2025-11-13

Jagadeesh kothha Jagadeesh kothha 

good
2025-11-10

ali gholaminezhad 

Please add case study project
2025-11-07

Sharma Manoj Kumar 

It was good
2025-11-06

Sakamuri Akhil Sai 

great
2025-11-04

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Scikit-learn is a Python library used for machine learning. More specifically, it's a set of – as the authors say – simple and efficient tools for data mining and data analysis. The framework is built on top of several popular Python packages, namely NumPy, SciPy, and matplotlib .