Deep Learning Fundamentals: Forward Model, Differentiable Loss Function & Optimization | SciPy 2019

Does deep learning feel like a mystical topic with a myriad of jargon? If so, then this tutorial is for you. We will dive deeply into the foundational ideas that power any deep learning model: a model specification, a differentiable loss function, and an optimization routine. To make the core and ancillary ideas concrete, we will be writing our own NumPy-based implementations of the relevant models and algorithms. By the end of the tutorial, your mastery of the foundational ideas should set you free to use