Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.

In this Specialization, you will build neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. You will master these theoretical concepts and their industry applications using Python and TensorFlow. You will tackle real-world case studies such as autonomous driving, sign language reading, music generation, computer vision, speech recognition, and natural language processing. AI is transforming many industries. The Deep Learning Specialization provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI. Along the way, you will get career advice from deep learning experts from industry and academia.