Modern World of Artificial Intelligence

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About Course

  • This course explores machine learning algorithms and applications, focusing on supervised and unsupervised learning techniques.
  • Students will learn the principles of machine learning, including model selection, training, evaluation, and optimization.
  • The course covers a range of algorithms, such as linear regression, decision trees, support vector machines, clustering, and neural networks, with hands-on experience using popular machine learning libraries.

What Will You Learn?

  • Implement machine learning models for both regression and classification tasks.
  • Apply unsupervised learning techniques such as clustering and dimensionality reduction.
  • Evaluate and optimize models using cross-validation, grid search, and hyperparameter tuning.
  • Understand and apply advanced machine learning techniques, including ensemble methods and deep learning.
  • Analyze and interpret the results of machine learning experiments in the context of real- world applications.

Course Content

Module 1: Deep Learning Architectures

Module 2: Deep Learning for NLP

Module 3: Recurrent Neural Networks (RNNs)

Live Sessions

Florida Coastal University

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