In her tech tutorial, Marina began with the fundamentals, guiding participants in creating neural network architectures from scratch and implementing both forward and backward propagation. The session covered essential optimization techniques, including gradient descent, weight initialization, and regularization. By the end of the tutorial, attendees gained a solid foundation in constructing and optimizing neural networks independently, without relying on deep learning frameworks. Marina's approach provided hands-on experience, fostering a deep understanding of the core principles behind neural network design and optimization.
This tutorial by Marina Marjanovic was held on November 21st as part of Tech Tutorials on Stream 5 live at the Data Science Conference Europe 2023.
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