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Machine Learning with scikit learn Course

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

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Lessons | 10

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93 Reviews

Sonal Zujam

The course was well-structured and beginner-friendly. The content was explained clearly, and the practical examples helped me understand the concepts better. Thank you for providing this learning opportunity.
2026-10-27

Ujjal kumar nath

Good
2026-09-20

Wiam Rajiby

Excellent course to understand scikit-learn fundamentals — helped me apply Random Forest classification to a real industrial predictive maintenance project.
2026-09-20

Nisha K

i am learn easy and useful to me
2026-09-20

Deepak

All Over Session Was Good
2026-09-05

Imthiyaz

Good
2026-08-31

Ahmad Turki

so greatful
2026-08-31

MUTASADDIK ALAM MUAZ

This was an amazing chapter , I love it .
2026-08-26

Rahul Saini

its satisfactory but need more deep dive into topics.
2026-08-23

Kholid Bisyri

realy good
2026-08-20

kolli Bhanu Teja

good to learn
2026-08-17

U. Y. N. S Sri Ramulu Undru

Good explain
2026-08-09

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Machine Learning with scikit learn Course Description

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 .