عنوان

Data science and predictive analytics :

شابک

3319723472

شابک

3319723480

شابک

9783319723471

شابک

9783319723488

شابک اشتباه

3319723464

شابک اشتباه

9783319723464

کد کشور

bnb

شماره

b624101

عنوان اصلي

Data science and predictive analytics :

نام عام مواد

[Book]

ساير اطلاعات عنواني

biomedical and health applications using R /

نام نخستين پديدآور

Ivo D. Dinov.

نام خاص و کميت اثر

1 online resource

متن يادداشت

1 Introduction -- 2 Foundations of R -- 3 Managing Data in R -- 4 Data Visualization -- 5 Linear Algebra & Matrix Computing -- 6 Dimensionality Reduction -- 7 Lazy Learning: Classification Using Nearest Neighbors -- 8 Probabilistic Learning: Classification Using Naive Bayes -- 9 Decision Tree Divide and Conquer Classification -- 10 Forecasting Numeric Data Using Regression Models -- 11 Black Box Machine-Learning Methods: Neural Networks and Support Vector Machines -- 12 Apriori Association Rules Learning -- 13 k-Means Clustering -- 14 Model Performance Assessment -- 15 Improving Model Performance -- 16 Specialized Machine Learning Topics -- 17 Variable/Feature Selection -- 18 Regularized Linear Modeling and Controlled Variable Selection -- 19 Big Longitudinal Data Analysis -- 20 Natural Language Processing/Text Mining -- 21 Prediction and Internal Statistical Cross Validation -- 22 Function Optimization -- 23 Deep Learning Neural Networks -- 24 Summary -- 25 Glossary -- 26 Index -- 27 Errata.

بدون عنوان

0

متن يادداشت

Over the past decade, Big Data have become ubiquitous in all economic sectors, scientific disciplines, and human activities. They have led to striking technological advances, affecting all human experiences. Our ability to manage, understand, interrogate, and interpret such extremely large, multisource, heterogeneous, incomplete, multiscale, and incongruent data has not kept pace with the rapid increase of the volume, complexity and proliferation of the deluge of digital information. There are three reasons for this shortfall. First, the volume of data is increasing much faster than the corresponding rise of our computational processing power (Kryder's law> Moore's law). Second, traditional discipline-bounds inhibit expeditious progress. Third, our education and training activities have fallen behind the accelerated trend of scientific, information, and communication advances.^There are very few rigorous instructional resources, interactive learning materials, and dynamic training environments that support active data science learning. The textbook balances the mathematical foundations with dexterous demonstrations and examples of data, tools, modules and workflows that serve as pillars for the urgently needed bridge to close that supply and demand predictive analytic skills gap. Exposing the enormous opportunities presented by the tsunami of Big data, this textbook aims to identify specific knowledge gaps, educational barriers, and workforce readiness deficiencies. Specifically, it focuses on the development of a transdisciplinary curriculum integrating modern computational methods, advanced data science techniques, innovative biomedical applications, and impactful health analytics.^The content of this graduate-level textbook fills a substantial gap in integrating modern engineering concepts, computational algorithms, mathematical optimization, statistical computing and biomedical inference. Big data analytic techniques and predictive scientific methods demand broad transdisciplinary knowledge, appeal to an extremely wide spectrum of readers/learners, and provide incredible opportunities for engagement throughout the academy, industry, regulatory and funding agencies.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix. 9783319723471

شماره استاندارد بين المللي کتاب و موسيقي

9783319723464

موضوع مستند نشده

Big data.

موضوع مستند نشده

Mathematical statistics.

موضوع مستند نشده

Medical records-- Data processing.

موضوع مستند نشده

R (Computer program language)

موضوع مستند نشده

Big Data.

موضوع مستند نشده

Big Data/Analytics.

موضوع مستند نشده

Data Mining and Knowledge Discovery.

موضوع مستند نشده

Health Informatics.

موضوع مستند نشده

Probability and Statistics in Computer Science.

موضوع مستند نشده

Big data.

موضوع مستند نشده

Business & Economics-- Industries-- Computer Industry.

موضوع مستند نشده

Business mathematics & systems.

موضوع مستند نشده

Computers-- Database Management-- Data Mining.

موضوع مستند نشده

Computers-- Database Management-- General.

موضوع مستند نشده

Computers-- Mathematical & Statistical Software.

موضوع مستند نشده

Data mining.

موضوع مستند نشده

Databases.

موضوع مستند نشده

Mathematical statistics.

موضوع مستند نشده

Maths for computer scientists.

موضوع مستند نشده

Medical equipment & techniques.

موضوع مستند نشده

Medical-- General.

موضوع مستند نشده

Medical records-- Data processing.

موضوع مستند نشده

R (Computer program language)

موضوع مستند نشده

COM021000

موضوع مستند نشده

UN

موضوع مستند نشده

UN

شماره

ويراست

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Dinov, Ivo D.

تاريخ عمليات

20201221083238.0

قواعد فهرست نويسي ( بخش توصيفي )

rda

نام الکترونيکي

نوع ماده

[Book]

کد کاربرگه

270410

تكميل شده

Y