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Scikit-learn Machine Learning with Python and SKlearn

Scikit-learn Machine Learning with Python and SKlearn

$9.99

$109.99

"Scikit-learn Machine Learning with Python and SKlearn" is a comprehensive course that introduces you to machine learning using the Scikit-learn library in Python. You'll learn to implement and evaluate both supervised and unsupervised learning models, build end-to-end machine learning solutions, and gain hands-on experience with real-world projects. By mastering Scikit-learn's features, you will be equipped to develop, train, and deploy effective machine learning models to solve complex data problems.

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Has discount
Expiry period Lifetime
Made in English
Last updated at Mon Jul 2024
Level
Beginner
Total lectures 28
Total quizzes 0
Total duration 07:40:24 Hours
Total enrolment 121
Number of reviews 24
Avg rating
Short description "Scikit-learn Machine Learning with Python and SKlearn" is a comprehensive course that introduces you to machine learning using the Scikit-learn library in Python. You'll learn to implement and evaluate both supervised and unsupervised learning models, build end-to-end machine learning solutions, and gain hands-on experience with real-world projects. By mastering Scikit-learn's features, you will be equipped to develop, train, and deploy effective machine learning models to solve complex data problems.
Outcomes
  • Scikit-learn Expertise: Proficiency in using Scikit-learn for implementing various machine learning algorithms and techniques.
  • Supervised Learning Skills: Ability to build and evaluate classification and regression models effectively.
  • Unsupervised Learning Capabilities: Skills in applying clustering and dimensionality reduction methods to uncover patterns in data.
  • Model Evaluation Techniques: Competence in assessing model performance, performing hyperparameter tuning, and applying cross-validation.
  • Practical ML Solutions: Experience in developing complete machine learning workflows, from data preprocessing to deploying models.
Requirements

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