This book focuses on Deep Learning (DL), which is an important aspect of data science, that includes predictive modelling. DL applications are widely used in domains such as finance, transport, health care, auto manufacturing, and advertising. The design of the DL models based on Artificial Neural Networks is influenced by the structure and operation of the brain. This book presents a comprehensive resource for those who seek a solid grasp of the techniques in DL.
- Provides knowledge on theory and design of state-of-the-art deep learning models for real-world applications.
- Explains the concepts and terminology in problem-solving with deep learning.
- Explores the theoretical basis for major algorithms and approaches in deep learning.
- Discusses the enhancement techniques of deep learning models.
- Identifies the performance evaluation techniques for deep learning models.