Frequently asked questions
Q: What is the difference between machine learning and deep learning?
A: Deep learning is a specialized implementation of machine learning as an abstract concept. Machine learning algorithms are primarily the functions that draw lines through the data points in the case of supervised learning algorithms. The feature space is mapped as a multi-dimensional representation. This representation generalizes the datasets and can predict the value or the state of the actor for new environment states. Deep learning algorithms also model the real-world data within the context. However, they take a layered approach in creating the models. Each layer in the network specializes in a specific part of the input signal, starting from the high-level, more generic features in the initial layers, to the deeper and granular features in the subsequent layers toward the output layer. These networks are capable of training themselves based on some of the popular algorithms, such as backpropagation...
