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Machine Learning AI

Track :

Programming

Lessons no : 11

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What will you learn in this course?
  • Develop and implement machine learning algorithms for real-world data analysis and prediction tasks using Python and popular libraries
  • Apply supervised, unsupervised, and reinforcement learning techniques to solve diverse AI problems effectively
  • Evaluate model performance using metrics like accuracy, precision, recall, and F1 score to optimize AI solutions
  • Design data preprocessing pipelines to clean, transform, and prepare datasets for machine learning models
  • Utilize feature engineering methods to enhance model accuracy and interpretability in AI applications
  • Implement cross-validation and hyperparameter tuning to improve machine learning model robustness and reliability
  • Integrate machine learning models into AI-driven applications for automation and decision-making processes
  • Analyze ethical considerations and biases in AI systems to develop fair and responsible machine learning solutions

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Lessons | 11


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Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy .