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Machine Learning with Scikit

Track :

Programming

Lessons no : 14

For Free Certificate After Complete The Course

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What will you learn in this course?
  • Develop and implement machine learning models using Scikit-learn for classification and regression tasks
  • Apply data preprocessing, feature engineering, and data visualization techniques with Scikit-learn, NumPy, and matplotlib
  • Evaluate model performance using metrics like accuracy, precision, recall, and F1-score in real-world scenarios
  • Utilize Scikit-learn's tools for hyperparameter tuning and model optimization to improve predictive accuracy
  • Build and deploy machine learning pipelines for scalable data analysis and automation
  • Identify appropriate algorithms and techniques for different data types and problem domains in machine learning
  • Interpret model results and insights to inform data-driven decision-making processes
  • Integrate Scikit-learn with other Python libraries for comprehensive data analysis and machine learning workflows

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  • Watch All Lessons
  • Watch at least 50% of Lesson Duration
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  • You can Register With Any Course For Free
  • The Certificate is free !
Lessons | 14

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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 .