Introduces deep learning fundamentals, covering data representations, neural networks, and convolutional neural networks.
Covers the back-propagation algorithm for deep neural networks and the importance of locality in CNN.
Introduces Convolutional Neural Networks (CNNs) for autonomous vehicles, covering architecture, applications, and regularization techniques.
Covers the fundamentals of deep learning, including data representations, bag of words, data pre-processing, artificial neural networks, and convolutional neural networks.
Explores deep learning fundamentals, including image classification, neural network working principles, and machine learning challenges.
