Keras is a deep learning library for fast, efficient training of deep learning models, and can also work with Tensorflow and Theano. Because it is lightweight and very easy to use, Keras has gained quite a lot of popularity in a very short time. This course will show you how to leverage the power of Keras to build and train high performance, high accuracy deep learning models, by implementing practical projects in real-world domains. Spanning over three hours, this course will help you master even the most advanced concepts in deep learning and how to implement them with Keras. You will train CNNs, RNNs, LSTMs, Autoencoders and Generative Adversarial Networks using real-world training datasets. These datasets will be from domains such as Image Processing and Computer Vision, Natural Language Processing, Reinforcement Learning and more. By the end of this highly practical course, you will be well-versed with deep learning and its implementation with Keras. By the end of this course, you will have all the knowledge you need to train your own deep learning models to solve different kinds of problems. Style and Approach: The course aims to explains the Deep Learning concepts in a simple, easy to understand manner and provides intuitive knowledge of the subjects. After you have grasped the concepts of a model, you will learn how to implement it with Keras.
Target Audience
This course is suitable for machine learning professionals and novices in deep learning who want to take their understanding of deep learning to the next level. While knowledge of the Keras framework is not required, it is assumed that you’re well versed with the machine learning concepts and Python programming language.
Business Outcomes
- Covers practical projects on building and training deep learning models with Keras
- Combines theory and practice, giving you a solid foundation to build your own Deep Leaning models
- Implement state of the art CNNs, RNNs, Autoencoders and Generative Adversarial Models
