TensorFlow 2 for Deep Learning Specialization

This Specialization is for machine learning practitioners and researchers who want to improve their skills using TensorFlow, a popular deep learning framework. This Specialization's first course will teach you the basics of building, training, evaluating, and making predictions using deep learning models. It also covers validating your models and includes regularisation, implementing callsbacks, saving and loading models. To develop customized deep learning models for any application, the second course will expand your TensorFlow knowledge. TensorFlow's lower-level APIs will be used to create complex model architectures and fully customized layers. You also have the ability to use flexible data workflows. Additionally, you will expand your TensorFlow API knowledge to include sequence models. The final course focuses on the ever-important probabilistic approach to deeplearning. TensorFlow will teach you how to create probabilistic models. This course makes use of the TensorFlow Probability Library, which allows you to easily combine probabilistic models and deep learning. This course can be considered an introduction to TensorFlow Probability Library. This Specialization requires knowledge of Python 3, deep learning concepts and machine learning, as well as a solid foundation in statistics and probability (especially course 3).