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Week - 1 |
Introduction to Machine Learning Fundamentals |
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Week - 2 |
EN: Setups, Intro to ML Concepts, Learning |
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Week - 3 |
EN: EN: EN: Model Accuracy Measurement |
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Week - 4 |
EN: EN: EN: EN: Simple and Multiple Linear Regression |
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Week - 5 |
EN: EN: EN: EN: Gradient Descent, KNN, Naive Bayes |
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Week - 6 |
Naive Bayes % Logistic Regression Projects |
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Week - 7 |
EN: EN: EN: EN: Logistic Regression, Model Performance Metrics, Model Selection, Regularization Techniques |
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Week - 8 |
EN: Midterm |
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Week - 9 |
EN: EN: EN: Boosting, Unsupervised Learning Case Studies: Applying Machine Learning in Real-World Scenarios |
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Week - 10 |
Practical Applications: Implementation of Machine Learning Models |
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Week - 11 |
EN: Support Vector Machines (SVM) |
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Week - 12 |
EN: Decision Trees, Random Forests |
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Week - 13 |
EN: Boosting, Unsupervised Learning |
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Week - 14 |
EN: Final Exam |
Eskisehir Technical University Info Package