this book has been drafted with unique approach the second edition focuses on the practicality of the topics within deep learning that help the reader to embrace modern tools with the right mathematical foundations the first edition focused on introducing meaningful foundation for the subjectwhile limiting the depth of the practical implementations while we explored breadth of technical frameworks for deep learning (theanotensorflowkerasand pytorch)we limited the depth of the implementation details the idea was to distill the mathematical foundations while focusing briefly on the practical tools used for implementation lot has changed over the past three years the deep learning fraternity is now stronger than everand the frameworks have evolved in size and adoption theano is now deprecated (ceased development)tensorflow saw huge adoption in the industry and academiaand keras became more popular among beginners and deep learning enthusiasts howeverpytorch has emerged recently as widely popular choice for academia as well as industry the growing number of research publications that recently have used pytorch over tensorflow is testament to its growth within deep learning on the same notewe felt the need to revise the book with focus on engaging readers with hands-on exercises to aid more meaningful understanding of the subject in this bookwe have struck the perfect balancewith mathematical foundations as well as hands-on exercisesto embrace practical implementation exclusively on pytorch each exercise is supplemented with the required explanations of pytorch' functionalities and required abstractions for programming complexities xv