Deep Learning A-Z: Hands-On Artificial Neural Networks

Project Description

This course is divided into two volumes, representing the two fundamental branches of Deep Learning: Supervised Deep Learning and Unsupervised Deep Learning. During this class real-world datasets are used to solve real-world business problems:

• Artificial Neural Networks to solve a customer churn problem
• Convolutional Neural Networks for image recognition
• Recurrent Neural Networks to predict stock prices
• Self-Organizing Maps to investigate fraud
• Boltzmann Machines to create a recomender system