Transformers for machine learning : a deep dive Transformers are becoming a core part of many neural network architectures employed in a wide range of applications such as NLP Speech Recognition Time Series and Computer Vision. Transformers have gone through many adaptations and alterations resulting in newer techniques and methods. Transformers for Machine Learning: A Deep Dive is the first comprehensive book on transformers. The theoretical explanations of the state of the art transformer architectures will appeal to postgraduate students and researchers (academic and industry) as it will provide a single entry point with deep discussions of a quickly moving field. The practical hands on case studies and code will appeal to undergraduate students practitioners and professionals as it allows for quick experimentation and lowers the barrier to entry into the field