Welcome to our book review site www.go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Bayesian Methodology: An overview with the help of R software
Bayesian methodology differs from traditional statistical methodology which involves frequentist approach. Bayesian methodology was introduced by Thomas Bayes (Statistician and minister at the Presbyterian Chapel) during the 18th Century. Bayesian methodology is now widely being used due to its simple, straightforward and interpretable characteristics of probability values and the efficiency of modern day computer systems. Bayesian methodology is now being used in the field of clinical research, clinical trials, epidemiology, econometrics, statistical process control, marketing research and statistical mechanics. It also used in the emerging field such as data science (machine learning and deep learning) and big data analytics. The book provides an overview of Bayesian methodology, its uses in different fields with the help of R statistical open source software. Editor International Journal of Statistics and Medical Informatics www.ijsmi.com/book.php
Deep Learning Models and its application: An overview with the help of R software: Second in series (Machine Learning)
Deep Learning Models and its application: An overview with the help of R softwarePrefaceDeep learning models are widely used in different fields due to its capability to handle large and complex datasets and produce the desired results with more accuracy at a greater speed. In Deep learning models, features are selected automatically through the iterative process wherein the model learns the features by going deep into the dataset and selects the features to be modeled. In the traditional models the features of the dataset needs to be specified in advance. The Deep Learning algorithms are derived from Artificial Neural Network concepts and it is a part of broader Machine Learning Models. Thi...
The Lancet
None
H-1B Handbook
None
Hospital Progress
None
