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Week - 1 |
Introduction, machine learning concepts, software tools |
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Week - 2 |
Basic probability and linear algebra review |
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Week - 3 |
Supervised learning, k-nearest neighbors (k-NN) |
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Week - 4 |
Linear methods |
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Week - 5 |
Naive Bayes classifier |
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Week - 6 |
Support vector machines (SVM) |
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Week - 7 |
Decision trees |
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Week - 8 |
Ensemble methods |
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Week - 9 |
Artificial neural networks |
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Week - 10 |
Dataset transformations, model evaluation, feature selection |
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Week - 11 |
Unsupervised methods |
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Week - 12 |
Clustering |
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Week - 13 |
Anomaly detection, principal component analysis (PCA) |
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Week - 14 |
Reinforcement learning, deep learning: convolutional neural networks, recurrent neural networks, autoencoders, generative models |
Eskisehir Technical University Info Package 
Turkish 
English