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Clinical Trial Management - an Overview
Clinical Trials word became a buzz word during this pandemic situation. It played a crucial role in developing vaccine to fight the pandemic. Experts from different fields contribute to the development of vaccine which includes (not limited) clinical researchers, health care providers, pharmaceutical industry, data managers, biostatisticians, data scientist and clinical trial programmers. Data collection, management, analysis and reporting also play an important role in helping decision makers in approving and rejecting the vaccine. This book provides an overview of clinical trial management process including protocol development, subject recruitment, professionals and organizations involved...
Digital Technologies – An overview of concepts, tools and techniques associated with it
Digital Technologies – An overview of concepts, tools and techniques associated with it Preface Digital technologies transformed the people’s day to day life and businesses organizations the way they work. It saved their time, accessibility and cost. It provided new opportunities, new markets, and new products to the organizations. Digital revolution started with the introduction of Computers, Internet, Mobile phones, Social media networks, Cloud computing, Big Data, Internet of Things, 3D Printing, Machine learning, Virtual reality, Natural Language Processing, Block Chain, Artificial Intelligence, Robotics and Quantum Computing. Digital technologies are so dynamic and it becomes diffic...
Ways to become successful in career: Required skill sets
Everyone wants to become successful in their career from fresher to senior level professionals. One need to build a career in a particular field or area based on their aims or ambitions or long time goals. Career building is a long process as it might take years and might be made up one job or multiple connected jobs or starting an own business or organization. If we choose and build a career in a field or area and move in that ladder then the journey will give greater job satisfaction, more confident, recognition, opportunities, sense of achievement, independence, security, reduce stress as we will be liking whatever we are doing and most importantly it will help us to grow financially. If ...
Introduction to Business Statistics through R software
Statistical methods are now widely used in different fields such as Business and Management, Economics, Biological, Physical sciences and including the new fields such as Data Science and Machine Learning. The data which form the basis for the statistical methods helps us to take scientific and informed decisions. Statistical methods deal with the collection, compilation, analysis and making inference from the data. This book deals with the statistical methods which are useful in Business and Management decision making. The methods include Probability, Sampling, Correlation, Regression and Hypothesis Testing, Time Series, Forecasting and Non-Parametric tests and advanced statistical models. The book uses open source R statistical software to carry out different statistical analysis with sample datasets. This book is third in series of Statistics books by the Author. Some of the contents are adopted from the author’s previous statistical book introduction to statistical methods and non-parametric methods.
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...
Machine Learning: An overview with the help of R software
This book intends to provide an overview of Machine Learning and its algorithms & models with help of R software. Machine learning forms the basis for Artificial Intelligence which will play a crucial role in day to day life of human beings in the near future. A basic understanding of machine learning is required, as its application is widely seen in different fields such as banks and financial sectors, manufacturing, aviation, transportation and medical field. The book covers machine learning classification algorithms such as K-Nearest Neighborhood, Naïve Bayes, Decision Trees and also Artificial Neural Networks and Support Vector Machines. It is recommended to refer author’s book on App...
Python programming for Data Scientists
Python programming language is an open source programming language which can be used under different operating system. Python programming redefined the programming concepts with its important features like flexibility, adaptability and reusability of codes. Python programming language has numerous libraries or modules which helps the programmer to save their time. The book starts with the overview of basic Python topics such as data structures, data types, conditions and controls, functions, lists, file handling and handling external datasets and database connections. The book also covers the topics in data science such as graphical and chart visualization, statistical modeling, text mining ...
Deep Learning Models explored with help of Python Programming
This is the second book in the Deep Learning models series by the author. Deep 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. The book starts w...
R Programming - A comprehensive guide
R programming has gained importance in different fields due its flexibility, rich packages, platform independent characteristics, data analysis & data visualization capabilities and building various models like machine learning models. It facilitates the incorporation of codes of other languages such as C, C++ and Java in its programming environment. R programming is an open source platform which is developed by Ross Ihaka and Robert Gentleman from University of Auckland during the year 1991. It is a modified version of S language developed during 1976 by Bell Laboratories in USA. Currently the development process is being handled by the R core development team. The book starts with the basi...
Application of statistical tools in biomedical domain: An overview with help of software
This book is an edited book from the papers of International Journal of Statistics and Medical Informatics authored by Editor, International of Statistics and Medical Informatics. It covers topics such as systematic review and meta-analysis, factor analysis, structural equation modelling and quantile regression in the field of biomedical domain. It also provides insight into the post hoc comparison, clinical trail data management and natural language processing
