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Machine Learning with scikit learn

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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Aditya Sandip Ghodke

good
2026-01-12

Manjit Pokhrel

it was good
2026-01-09

R.KEERTHANA

Good
2026-01-07

S LAKSHMI

good
2026-01-06

Nersiya Vensi J

Nice
2026-01-06

Jamshaid Aslam

I have successfully completed the Machine Learning course on Mind Luster.
The course content was well structured and easy to understand for beginners.
Concepts like supervised learning, unsupervised learning, algorithms, and real-life examples were explained clearly.
This course helped me build a strong foundation in Machine Learning and increased my confidence.
I highly recommend this course to students and beginners who want to start Machine Learning.
2026-01-04

P. Kaviya

Useful
2026-01-03

Shiv

good course
2025-12-24

Sayali Vaidya

It excellent I understand all things and it makes easy to me learn machine learning in details
2025-12-23

Avaniy V

it was very much useful
2025-12-08

DEEKSHA JAIN SR

GOOD
2025-12-02

Nandani Chaudhary

Great
2025-12-01

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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 .