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Deep dive into the mathematics and theory behind modern AI
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Apply concepts from linear algebra and calculus to understand ML algorithms
Implement and train machine learning models using libraries like TensorFlow or PyTorch
Understand the architecture of neural networks, including layers, activation functions, and backpropagation
Analyze and optimize model performance through hyperparameter tuning and validation techniques
Conduct independent research, formulate a hypothesis, and present findings in a formal paper
Independent Research Paper & Presentation: Students undertake a novel research project, applying advanced ML techniques to a dataset and formally presenting their methods and results.