Data Analytics for Drilling Engineering: Theory, Algorithms, Experiments, Software (Information Fusion and Data Science) [1st ed. 2020] 9783030340353, 9783030340346, 303034035X

Data Science and Productivity Analytics [1st ed.] 9783030433833, 9783030433840

This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and dat

452 66 10MB Read more

Software Engineering for Data Scientists (MEAP V03)

These easy to learn and apply software engineering techniques will radically improve collaboration, scaling, and deploym

190 50 5MB Read more

Data Science for Entrepreneurship: Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society 3031195531, 9783031195532

The fast-paced technological development and the plethora of data create numerous opportunities waiting to be exploited

171 36 17MB Read more

Graph Algorithms for Data Science (MEAP v7)

Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques

207 101 10MB Read more

Graph Algorithms for Data Science MEAP V08

Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques

176 29 10MB Read more

Visual Analytics for Data Scientists [1st ed.] 9783030561451, 9783030561468

This textbook presents the main principles of visual analytics and describes techniques and approaches that have proven

353 118 82MB Read more

Theory and Algorithms for Information Extraction and Classification in Textual Data Mining

Regular expressions can be used as patterns to extract features from semi-structured and narrative text [8]. For example

392 81 77KB Read more

Data Science and Analytics for Ordinary People 9781329280625

439 5 3MB Read more

Theory and Technology of Drilling Engineering [1st ed.] 9789811593260, 9789811593277

This book presents the theory and technologies of drilling operations. It covers the gamut of formulas and calculations

437 93 17MB Read more

Data Driven Science & Engineering

Data Driven Science & Engineering. 2017.

203 49 69MB Read more