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Web Based Machine Learning Analytics System In Big Data

Web Based Machine Learning Analytics System in Big Data PDF
Author: Mingchu King
Publisher:
Release: 2018-08-11
ISBN: 9781718120051
Size: 44.72 MB
Format: PDF, ePub, Docs
Category :
Languages : en
Pages : 257
View: 5328

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Web Based Machine Learning Analytics System In Big Data

by Mingchu King, Web Based Machine Learning Analytics System In Big Data Books available in PDF, EPUB, Mobi Format. Download Web Based Machine Learning Analytics System In Big Data books, This book is dedicated to people who have the aspiration to build their own analytics system with the capability of interactive user interface, machine learning, and in NOSQL database.This book provides detailed guidance and code examples to implement a web-based interactive applications and machine learning system through seamless integration of Django, Tensorflow, Keras, HTML, Javascript, CSS, and Cassandra. There are four parts in this book. Foundations provides fundamental knowledge to understand the basic elements of each part to be integrated as a system. Application development introduces how to build an interactive web application, the machine learning libraries, and how to build machine learning applications. Big-Data database integration introduces Cassandra and how to integrate Cassandra into Django applications. Responsive Web-based analytics application provides real code examples how to develop applications for data modeling, investment dashboard with responsive charts, and interactive Convolution Neural Network application.FoundationsChapter 1: Python Basics Chapter 2: Machine Learning using Tensorflow and Keras Chapter 3: HTML, CSS, and Javascript Chapter 4: Django Framework Application DevelopmentChapter 5: Interactive Web Application Chapter 6: Integrate Machine Learning Libraries and Build Applications Big-Data Database IntegrationChapter 7: Cassandra Introduction and Installation Chapter 8: Integrating Cassandra with DjangoResponsive Web-Based Analytics Applications Chapter 9: Data Modeling Chapter 10: Investment Dashboard and Responsive Charts Chapter 11: Interactive Convolution Neural Network ApplicationChapter 12: Summary



Intelligent Systems In Big Data Semantic Web And Machine Learning

Intelligent Systems in Big Data  Semantic Web and Machine Learning PDF
Author: Noreddine Gherabi
Publisher: Springer
Release: 2021-05-29
ISBN: 9783030725877
Size: 77.48 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 315
View: 6039

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Intelligent Systems In Big Data Semantic Web And Machine Learning

by Noreddine Gherabi, Intelligent Systems In Big Data Semantic Web And Machine Learning Books available in PDF, EPUB, Mobi Format. Download Intelligent Systems In Big Data Semantic Web And Machine Learning books, This book describes important methodologies, tools and techniques from the fields of artificial intelligence, basically those which are based on relevant conceptual and formal development. The coverage is wide, ranging from machine learning to the use of data on the Semantic Web, with many new topics. The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. The book is meant to be a very important and useful source of information for researchers and doctoral students in data analysis, Semantic Web, big data, machine learning, computer engineering and related disciplines, as well as for postgraduate students who want to integrate the doctoral cycle.



Practical Big Data Analytics

Practical Big Data Analytics PDF
Author: Nataraj Dasgupta
Publisher: Packt Publishing Ltd
Release: 2018-01-15
ISBN: 1783554401
Size: 49.62 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 412
View: 733

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Practical Big Data Analytics

by Nataraj Dasgupta, Practical Big Data Analytics Books available in PDF, EPUB, Mobi Format. Download Practical Big Data Analytics books, Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.



Advancing The Power Of Learning Analytics And Big Data In Education

Advancing the Power of Learning Analytics and Big Data in Education PDF
Author: Azevedo, Ana
Publisher: IGI Global
Release: 2021-03-19
ISBN: 1799871045
Size: 27.74 MB
Format: PDF, ePub
Category : Education
Languages : en
Pages : 296
View: 4171

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Advancing The Power Of Learning Analytics And Big Data In Education

by Azevedo, Ana, Advancing The Power Of Learning Analytics And Big Data In Education Books available in PDF, EPUB, Mobi Format. Download Advancing The Power Of Learning Analytics And Big Data In Education books, The term learning analytics is used in the context of the use of analytics in e-learning environments. Learning analytics is used to improve quality. It uses data about students and their activities to provide better understanding and to improve student learning. The use of learning management systems, where the activity of the students can be easily accessed, potentiated the use of learning analytics to understand their route during the learning process, help students be aware of their progress, and detect situations where students can give up the course before its completion, which is a growing problem in e-learning environments. Advancing the Power of Learning Analytics and Big Data in Education provides insights concerning the use of learning analytics, the role and impact of analytics on education, and how learning analytics are designed, employed, and assessed. The chapters will discuss factors affecting learning analytics such as human factors, geographical factors, technological factors, and ethical and legal factors. This book is ideal for teachers, administrators, teacher educators, practitioners, stakeholders, researchers, academicians, and students interested in the use of big data and learning analytics for improved student success and educational environments.



Python Real World Data Science

Python  Real World Data Science PDF
Author: Dusty Phillips
Publisher: Packt Publishing Ltd
Release: 2016-06-10
ISBN: 1786468417
Size: 22.22 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 1255
View: 7572

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Python Real World Data Science

by Dusty Phillips, Python Real World Data Science Books available in PDF, EPUB, Mobi Format. Download Python Real World Data Science books, Unleash the power of Python and its robust data science capabilities About This Book Unleash the power of Python 3 objects Learn to use powerful Python libraries for effective data processing and analysis Harness the power of Python to analyze data and create insightful predictive models Unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Who This Book Is For Entry-level analysts who want to enter in the data science world will find this course very useful to get themselves acquainted with Python's data science capabilities for doing real-world data analysis. What You Will Learn Install and setup Python Implement objects in Python by creating classes and defining methods Get acquainted with NumPy to use it with arrays and array-oriented computing in data analysis Create effective visualizations for presenting your data using Matplotlib Process and analyze data using the time series capabilities of pandas Interact with different kind of database systems, such as file, disk format, Mongo, and Redis Apply data mining concepts to real-world problems Compute on big data, including real-time data from the Internet Explore how to use different machine learning models to ask different questions of your data In Detail The Python: Real-World Data Science course will take you on a journey to become an efficient data science practitioner by thoroughly understanding the key concepts of Python. This learning path is divided into four modules and each module are a mini course in their own right, and as you complete each one, you'll have gained key skills and be ready for the material in the next module. The course begins with getting your Python fundamentals nailed down. After getting familiar with Python core concepts, it's time that you dive into the field of data science. In the second module, you'll learn how to perform data analysis using Python in a practical and example-driven way. The third module will teach you how to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis to more complex data types including text, images, and graphs. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. In the final module, we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls. Style and approach This course includes all the resources that will help you jump into the data science field with Python and learn how to make sense of data. The aim is to create a smooth learning path that will teach you how to get started with powerful Python libraries and perform various data science techniques in depth.



Big Data And Learning Analytics In Higher Education

Big Data and Learning Analytics in Higher Education PDF
Author: Ben Kei Daniel
Publisher: Springer
Release: 2016-08-27
ISBN: 3319065203
Size: 49.64 MB
Format: PDF, ePub, Docs
Category : Education
Languages : en
Pages : 272
View: 1985

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Big Data And Learning Analytics In Higher Education

by Ben Kei Daniel, Big Data And Learning Analytics In Higher Education Books available in PDF, EPUB, Mobi Format. Download Big Data And Learning Analytics In Higher Education books, ​This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning​. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns​.



Social Network Forensics Cyber Security And Machine Learning

Social Network Forensics  Cyber Security  and Machine Learning PDF
Author: P. Venkata Krishna
Publisher: Springer
Release: 2018-12-29
ISBN: 981131456X
Size: 61.90 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 116
View: 6369

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Social Network Forensics Cyber Security And Machine Learning

by P. Venkata Krishna, Social Network Forensics Cyber Security And Machine Learning Books available in PDF, EPUB, Mobi Format. Download Social Network Forensics Cyber Security And Machine Learning books, This book discusses the issues and challenges in Online Social Networks (OSNs). It highlights various aspects of OSNs consisting of novel social network strategies and the development of services using different computing models. Moreover, the book investigates how OSNs are impacted by cutting-edge innovations.



Machine Intelligence And Big Data Analytics For Cybersecurity Applications

Machine Intelligence and Big Data Analytics for Cybersecurity Applications PDF
Author: Yassine Maleh
Publisher: Springer Nature
Release: 2020-12-14
ISBN: 303057024X
Size: 73.61 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 539
View: 1288

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Machine Intelligence And Big Data Analytics For Cybersecurity Applications

by Yassine Maleh, Machine Intelligence And Big Data Analytics For Cybersecurity Applications Books available in PDF, EPUB, Mobi Format. Download Machine Intelligence And Big Data Analytics For Cybersecurity Applications books, This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field. Bridging an important gap between machine intelligence, big data, and cybersecurity communities, it aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances on machine intelligence and big data analytics for cybersecurity applications.



Big Data

Big Data PDF
Author: Viktor Mayer-Schönberger
Publisher: Redline Wirtschaft
Release: 2013-10-08
ISBN: 3864144590
Size: 26.84 MB
Format: PDF, ePub, Mobi
Category : Political Science
Languages : de
Pages : 288
View: 485

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Big Data

by Viktor Mayer-Schönberger, Big Data Books available in PDF, EPUB, Mobi Format. Download Big Data books, Ob Kaufverhalten, Grippewellen oder welche Farbe am ehesten verrät, ob ein Gebrauchtwagen in einem guten Zustand ist – noch nie gab es eine solche Menge an Daten und noch nie bot sich die Chance, durch Recherche und Kombination in der Daten¬flut blitzschnell Zusammenhänge zu entschlüsseln. Big Data bedeutet nichts weniger als eine Revolution für Gesellschaft, Wirtschaft und Politik. Es wird die Weise, wie wir über Gesundheit, Erziehung, Innovation und vieles mehr denken, völlig umkrempeln. Und Vorhersagen möglich machen, die bisher undenkbar waren. Die Experten Viktor Mayer-Schönberger und Kenneth Cukier beschreiben in ihrem Buch, was Big Data ist, welche Möglichkeiten sich eröffnen, vor welchen Umwälzungen wir alle stehen – und verschweigen auch die dunkle Seite wie das Ausspähen von persönlichen Daten und den drohenden Verlust der Privatsphäre nicht.



Predictive Analytics With Microsoft Azure Machine Learning 2nd Edition

Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition PDF
Author: Valentine Fontama
Publisher: Apress
Release: 2015-08-26
ISBN: 1484212002
Size: 28.36 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 291
View: 4192

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Predictive Analytics With Microsoft Azure Machine Learning 2nd Edition

by Valentine Fontama, Predictive Analytics With Microsoft Azure Machine Learning 2nd Edition Books available in PDF, EPUB, Mobi Format. Download Predictive Analytics With Microsoft Azure Machine Learning 2nd Edition books, Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models. The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services. Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft. What’s New in the Second Edition? Five new chapters have been added with practical detailed coverage of: Python Integration – a new feature announced February 2015 Data preparation and feature selection Data visualization with Power BI Recommendation engines Selling your models on Azure Marketplace