English | 2021 | ISBN: 1119669367 | 291 pages | True PDF | 13.91 MB
Jump-start your career as a data scientist-learn to develop datasets for exploration, analysis, and machine learning
SQL for Data Scientists:A Beginner's Guide for Building Datasets for Analysisis a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls.

E. Michael Nussbaum, "Categorical and Nonparametric Data Analysis: Choosing the Best Statistical Technique"
English | ISBN: 1138787825 | 2014 | 526 pages | PDF | 6 MB
Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain their assumptions and how tests work in future publications. Numerous examples from psychology, education, and other social sciences demonstrate varied applications of the material. Basic statistics and probability are reviewed for those who need a refresher. Mathematical derivations are placed in optional appendices for those interested in this detailed coverage.

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 216 Lessons (28h) | Size: 10.6 GB
This intermediate VMware Certified Professional - Data Center Virtualization 2021 training prepares virtualization specialists to take the 2V0-21.20 exam, which is the one exam required to earn the VCP-DCV 2021 certification.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 36 lectures (15h 17m) | Size: 4.3 GB
Complete Stats :Central Limit,Z-Score,Confidence Interval,Hypothesis,T-Test,Chi-Square,AnOva,Regression and Much More!

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
2021 | ISBN: 9781801071413 | English
Duration: 21 Lessons (2h 49m) | Size: 1.22 GB

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 29 lectures (5h 18m) | Size: 2.45 GB
Data Migration to S/4 Hana with Green Field Implementation Approach

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 34 lectures (5h 46m) | Size: 2.33 GB
Data Extraction - Data Cleaning - Data Analysis

Models of Computation for Big Data by Rajendra Akerkar
English | EPUB | 2018 | 110 Pages | ISBN : 3319918508 | 6.8 MB
The big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms and the underlying mathematical techniques. There is a need to understand foundational strengths and address the state of the art challenges in big data that could lead to practical impact. The main goal of this book is to introduce algorithmic techniques for dealing with big data sets. Traditional algorithms work successfully when the input data fits well within memory. In many recent application situations, however, the size of the input data is too large to fit within memory.

English | 2021 | ISBN: 1636391524 | 147 pages | True PDF | 62.51 MB
When you picture human-data interactions (HDI), what comes to mind? The datafication of modern life, along with open data initiatives advocating for transparency and access to current and historical datasets, has fundamentally transformed when, where, and how people encounter data. People now rely on data to make decisions, understand current events, and interpret the world. We frequently employ graphs, maps, and other spatialized forms to aid data interpretation, yet the familiarity of these displays causes us to forget that even basic representations are complex, challenging inscriptions and are not neutral; they are based on representational choices that impact how and what they communicate. This book draws on frameworks from the learning sciences, visualization, and human-computer interaction to explore embodied HDI. This exciting sub-field of interaction design is based on the premise that every day we produce and have access to quintillions of bytes of data, the exploration and analysis of which are no longer confined within the walls of research laboratories. This volume examines how humans interact with these data in informal (not work or school) environments, paritcularly in museums.
[b]The first half of the book provides an overview of the multi-disciplinary, theoretical foundations of HDI (in particular, embodied cognition, conceptual metaphor theory, embodied interaction, and embodied learning) and reviews socio-technical theories relevant for designing HDI installations to support informal learning. The second half of the book describes strategies for engaging museum visitors with interactive data visualizations, presents methodologies that can inform the design of hand gestures and body movements for embodied installations, and discusses how HDI can facilitate people's sensemaking about data.

English | 2021 | ISBN: 1119811554 | 435 pages | True PDF | 16.95 MB
Make smart business decisions with your data by design!
Take a deep dive to understand how developing your data science dogma can drive your business―ya dig? Every phone, tablet, computer, watch, and camera generates data―we're overwhelmed with the stuff. That's why it's become increasingly important that you know how to derive useful insights from the data you have to understand which piece of data in the sea of data is important and which isn't (trust us: not as scary as it sounds!), and to rely on said data to make critical business decisions. Enter the world of data science: the practice of using scientific methods, processes, and algorithms to gain knowledge and insights from any type of data.