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Practical Machine Learning

Track :

Programming

Lessons no : 72

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What will you learn in this course?
  • Develop practical skills in implementing supervised and unsupervised machine learning algorithms using Python and popular libraries
  • Apply data preprocessing, feature engineering, and model evaluation techniques to real-world datasets in machine learning projects
  • Design and build predictive models for classification and regression tasks with Python machine learning tools
  • Utilize clustering, dimensionality reduction, and anomaly detection methods for unsupervised learning applications
  • Interpret machine learning model results to derive actionable insights for business decision-making and data analysis
  • Implement cross-validation and hyperparameter tuning to optimize machine learning model performance
  • Identify appropriate machine learning techniques for different data types and problem domains using Python
  • Develop end-to-end machine learning workflows, including data collection, cleaning, modeling, and deployment

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Lessons | 72
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Dibyajit Das

Good 2025-03-18

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