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Explore the intricacies of feature engineering and model training in this 32-minute talk from the EuroPython 2018 Conference. Delve into strategies for handling low-dimensional data and learn when manual feature engineering can significantly improve model performance. Follow along as Alisa Dammer presents a sample classification problem using neural networks, demonstrating practical techniques to enhance data utilization. Gain insights applicable to various data science tasks, with a focus on maximizing the potential of limited datasets. Access accompanying materials, including slides, Jupyter notebooks, test and train sets, and neural network configuration files, on the provided GitHub repository for hands-on learning and further exploration.