| Learning Outcomes |
At the end of this course, the students;
- Explain the fundamental concepts, relationships, and differences regarding artificial intelligence, machine learning, and deep learning.
- Explain the operating principles of basic and advanced deep learning architectures based on artificial neural networks and apply them to appropriate problem types.
- Perform data preparation, model creation, training, and testing processes using deep learning libraries.
- Evaluate the performance of deep learning models, identify overfitting issues, and analyze and interpret the results of models developed for real-world problems.
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