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Understanding the Role of Business Analytics
This book encompasses empirical evidences to understand the application of data analytical techniques in emerging contexts. Varied studies relating to manufacturing and services sectors including healthcare, banking, information technology, power, education sector etc. stresses upon the systematic approach followed in... | | Practical DataOps: Delivering Agile Data Science at Scale
Gain a practical introduction to DataOps, a new discipline for delivering data science at scale inspired by practices at companies such as Facebook, Uber, LinkedIn, Twitter, and eBay. Organizations need more than the latest AI algorithms, hottest tools, and best people to turn data into insight-driven action and useful ... | | |
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| | Sequence Data Mining (Advances in Database Systems)
Sequences are an important type of data which occur frequently in many scientific,
medical, security, business and other applications. For example, DNA
sequences encode the genetic makeup of humans and all species, and protein
sequences describe the amino acid composition of proteins and encode
the structure and function of... | | Developing Microservices with Node.js
Key Features
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Real world example explained chapter after chapter with code examples.
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Useful concepts for other languages like Java or PHP
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Easy to follow by people with little to none experience in Node.js
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Node.js Version 0.12.2 and the latest compatible versions of Seneca and
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The Conductive Organization: Building Beyond SustainabilityAn organization's culture lies at the heart of its ability to perform. In the knowledge economy, new rules are emerging and organizations must rethink how they will compete by leveraging their tacit knowledge - their intangible assets - in order to create and sustain a strategic advantage. In this book, Hubert Saint-Onge and Charles Armstrong, two... | | | | Introduction to Machine Learning (Adaptive Computation and Machine Learning)The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed... |
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