Instant download Data Science From Research to Application pdf, docx, kindle format all chapters after payment. 3030373088, 9783030373085
Product details:
ISBN 10: 3030373088
ISBN 13: 9783030373085
Author: Springer
This book presents outstanding theoretical and practical findings in data science and associated interdisciplinary areas. Its main goal is to explore how data science research can revolutionize society and industries in a positive way, drawing on pure research to do so. The topics covered range from pure data science to fake news detection, as well as Internet of Things in the context of Industry 4.0. Data science is a rapidly growing field and, as a profession, incorporates a wide variety of areas, from statistics, mathematics and machine learning, to applied big data analytics. According to Forbes magazine, “Data Science” was listed as LinkedIn’s fastest-growing job in 2017. This book presents selected papers from the International Conference on Contemporary Issues in Data Science (CiDaS 2019), a professional data science event that provided a real workshop (not “listen-shop”) where scientists and scholars had the chance to shareideas, form new collaborations, and brainstorm on major challenges; and where industry experts could catch up on emerging solutions to help solve their concrete data science problems. Given its scope, the book will benefit not only data scientists and scientists from other domains, but also industry experts, policymakers and politicians.
Table of contents:
Efficient Cluster Head Selection Using the Non-linear Programming Method for Wireless Sensor Networks
A Survey on Measurement Metrics for Shape Matching Based on Similarity, Scaling and Spatial Distance
Static Signature-Based Malware Detection Using Opcode and Binary Information
RSS_RAID a Novel Replicated Storage Schema for RAID System
A New Distributed Ensemble Method with Applications to Machine Learning
A Glance on Performance of Fitness Functions Toward Evolutionary Algorithms in Mutation Testing
Density Clustering Based Data Association Approach for Tracking Multiple Targets in Cluttered Environment
Representation Learning Techniques: An Overview
A Community Detection Method Based on the Subspace Similarity of Nodes in Complex Networks
Forecasting Multivariate Time-Series Data Using LSTM and Mini-Batches
Identifying Cancer-Related Signaling Pathways Using Formal Methods
Predicting Liver Transplantation Outcomes Through Data Analytics
Deep Learning Prediction of Heat Propagation on 2-D Domain via Numerical Solution
Cluster Based User Identification and Authentication for the Internet of Things Platform
Forecasting of Customer Behavior Using Time Series Analysis
Correlation Analysis of Applications’ Features: A Case Study on Google Play
Information Verification Enhancement Using Entailment Methods
A Clustering Based Approximate Algorithm for Mining Frequent Itemsets
Next Frame Prediction Using Flow Fields
Using Augmented Genetic Algorithm for Search-Based Software Testing
Building and Exploiting Lexical Databases for Morphological Parsing
A Novel Topological Descriptor for ASL
Pairwise Conditional Random Fields for Protein Function Prediction
Adversarial Samples for Improving Performance of Software Defect Prediction Models
A Systematic Literature Review on Blockchain-Based Solutions for IoT Security
An Intelligent Safety System for Human-Centered Semi-autonomous Vehicles
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