Imagine if you had built an artificial life simulator, and you sample a different neural network to control the behavior of each ant inside an ant colony. Using the Simple Evolution Strategy for this task will optimise for traits and behaviours that benefit individual ants, and with each successive generation, our population will be full of alpha ants who only care about their own well-being.A Visual Guide to Evolution Strategies
When we train neural networks we usually use Gradient Descent to optimize the weights. At each iteration we use back-propagation to calculate the derivative of the loss function with respect to each weight and subtract it from that weight. Learning rate determines how quickly or how slowly you want to update your weight(parameter) values.Everything you need to know about Neural Networks
At Uber, event forecasting enables us to future-proof our services based on anticipated user demand. The goal is to accurately predict where, when, and how many ride requests Uber will receive at any given time.Engineering Extreme Event Forecasting at Uber with Recurrent Neural Networks
