R Deep Learning Essentials
Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
Build models relating to neural
Bioinformatics: Converting Data to Knowledge, Workshop Summary In 1993 the National Research Council’s Board on Biology established a series of forums on biotechnology. The purpose of the discussions is to foster open communication among scientists, administrators, policy-makers, and others engaged in biotechnology research, development, and commercialization. The neutral setting offered by the National...
Food Allergy: Adverse Reaction to Foods and Food Additives
Edited by world-renowned experts in the field, Food Allergy covers pediatric and adult adverse reactions to foods and food additives in one comprehensive volume. Designed to be a practical, readable reference for use in the hospital or private practice setting, the text is organized into five sections covering basic and clinical...
Gas Explosion Technology and Biomass Refinery
The book introduces gas explosion technology (GET) and its applications in biomass refineries. In this book an overview of GET is provided, the mechanisms are thoroughly discussed. The chapters also cover the latest processes and equipments of GET, including equipment selection, parameter determination and engineering scaling-up. Last but not...
Genomics, Proteomics and Vaccines
While the sequence of the human genome sequence has hit the headlines, extensive exploitation of this for practical applications is still to come. Genomic and post-genomic technologies applied to viral and bacterial pathogens, which are almost equally important from a scientific perspective, have the potential to be translated into useful...
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