<ul><li>This article takes you back to the roots of deep learning through a simple problem statement, unraveling its origins.</li><li>A quantitative analyst at a hedge fund needs to develop a trading signal based on news sentiment to classify market sentiment as bullish or bearish.</li><li>Weights and bias are introduced to improve the accuracy of the model in classifying market sentiment.</li><li>The article discusses the concept of a perceptron learning algorithm and the evolution of decision boundaries in capturing market patterns.</li></ul>

Curious About AI? Here’s the Deep Learning Story You Need to Know

Discover more