Pytorch Against Tumor

With this publication, we finally have a definitive treatise on PyTorch. It covers the basics and abstractions in great detail.
From the Foreword by Soumith Chintala, Cocreator of PyTorch

This book tells the story of the discovery of microRNA (miRNA) quantum code, the basic theory of biological data science for medical investigation with miRNA, to its implementation. It explains the use of a new algorithm called the miRNA entangling target sorter (METS), based on the quantum computation algorithm, to give the etiologic analysis for diseases such as cancer, infectious diseases, and age-related disorders. Providing detailed descriptions to make the METS algorithm simple to grasp, it also explains the accumulated cutting-edged data for human diseases utilizing artificial intelligence (AI) for quantum miRNA language (miRNA qubit) (MIRAI). Further, it describes a discovery story for quantum miRNA surveillance against tumors and quantum miRNA immunity against viruses. Since this is a multidisciplinary field of study, crucial details on physics, mathematics, computer science, data science, virology, immunology, oncology, pathology, and biology are supplied.

Master advanced techniques and algorithms for machine learning with PyTorch using real-world examples

Key Features
Understand how to use PyTorch to build advanced neural network models including graph neural networks and reinforcement learning models