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Machine Learning

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Course Description

  • Machine learning is a field of study that enables machines to learn from data and improve their performance on a task with experience.
  • This short course provides an overview of the fundamental concepts, techniques, and algorithms in machine learning.
  • Topics covered include supervised learning, unsupervised learning, and reinforcement learning, as well as common machine learning models such as decision trees, logistic regression, and neural networks.
  • Participants will learn how to formulate a machine learning problem, collect and preprocess data, design a model, train it on data, and evaluate its performance.
  • The course also covers popular machine learning tools such as Python libraries like scikit-learn and TensorFlow. By the end of the course, participants will have a solid understanding of the key concepts and techniques in machine learning and the ability to apply them to real-world problems in a variety of domains.
  • By the end of the course, participants will have a solid understanding of the key concepts and techniques in machine learning and the ability to apply them to real-world problems in a variety of domains.
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