Sponsored by Amazon.
Understanding how to create a deep learning neural network is an essential component of any data scientist's knowledge base. This course covers some of the challenges that arise when training neural networks. It focuses on the problem of overfitting and its potential remedy: regularization. Learners should have a basic understanding of linear algebra and calculus.
Laura Graesser is assisting in NVIDIA's autonomous driving project. Previously with The Boston Consulting Group, Laura is a graduate student at New York University, where she's working toward a master’s degree in computer science and machine learning. Laura's interests include neural networks and their application to computer vision problems, and the cross-fertilization between computer vision and natural language processing.