big data and machine learning pdf

Big Data And Machine Learning Pdf

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This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. The possible challenges in this direction include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy.

Data Mining, Machine Learning and Big Data Analytics

Outpatients who fail to attend their appointments have a negative impact on the healthcare outcome. Thus, healthcare organizations facing new opportunities, one of them is to improve the quality of healthcare Citation: Journal of Big Data 7 Content type: Research.

Published on: 9 December A massive amount of data is generated with the evolution of modern technologies. This high-throughput data generation results in Big Data, which consist of many features attributes. However, irrelevant featu Authors: A. Sikos and Paul Haskell-Dowland. Published on: 4 December The Correction to this article has been published in Journal of Big Data 7 Flight delay is inevitable and it plays an important role in both profits and loss of the airlines.

An accurate estimation of flight delay is critical for airlines because the results can be applied to increas Published on: 26 November Computer networks intrusion detection systems IDSs and intrusion prevention systems IPSs are critical aspects that contribute to the success of an organization.

Authors: Sydney M. Kasongo and Yanxia Sun. Published on: 25 November The exponential growth in computer networks and network applications worldwide has been matched by a surge in cyberattacks. Authors: Joffrey L. Leevy and Taghi M. Content type: Survey Paper. Published on: 23 November The amount of data produced by sensors, social and digital media, and Internet of Things IoTs are rapidly increasing each day.

Decision makers often need to sift through a sea of Big Data to utilize informat Authors: Tian J. Ma, Rudy J. Content type: Methodology. Published on: 17 November Sorting algorithms are among the most commonly used algorithms in computer science and modern software. Having efficient implementation of sorting is necessary for a wide spectrum of scientific applications. Authors: Marek Nowicki. Published on: 16 November In recent years, deep learning has become one of the most important topics in computer sciences.

Deep learning is a growing trend in the edge of technology and its applications are now seen in many aspects of Published on: 12 November Fog computing architecture is referred to the architecture that is distributed over the geographical area. This architectural arrangement mainly focuses on physical and logical network elements, and software f Authors: Amr Adel.

Object detection and gender recognition were two different categories to be classified in a single section is a complicated task and this approach helps in supporting the blind people for an artificial vision Published on: 11 November In the light of the recent technological advances in computing and data explosion, the complex interactions of the Sustainable Development Goals SDG present both a challenge and an opportunity to researchers Authors: Kassim S.

Mwitondi, Isaac Munyakazi and Barnabas N. Authors: Pradeep S. Published on: 10 November Organizations may be related in terms of similar operational procedures, management, and supervisory agencies coordinating their operations.

Supervisory agencies may be governmental or non-governmental but, in Authors: Patrick Obilikwu and Emeka Ogbuju. Researchers should be familiar with the strengths and weaknesses of current implementations of Authors: John T.

Hancock and Taghi M. Published on: 4 November Along with the big data era, digital transformation has had a transformative effect on modern education tremendously in higher education. It transforms an institutional core value of education to better meet s Authors: Young-Eun Park. Published on: 21 October A modern urban infrastructure no longer operates in isolation, but instead, leverages the latest technologies to collect, process, and distribute aggregated knowledge in order to improve the quality of the pro Classification of data points which correspond to complex entities such as people or journal articles is a ongoing research task.

Notable applications are recommendation systems for customer behaviors based up Authors: Phuong Pho and Alexander V. Published on: 20 October Argumentation mining is a research field which focuses on sentences in type of argumentation.

Argumentative sentences are often used in daily communication and have important role in each decision or conclusio Published on: 19 October In manufacturing processes, datasets intended for data driven decisions are majorly generated from time-sequenced sensor readings.

Industrial sensor systems are prone to transmit inaccurate readings, which res Authors: Omogbai Oleghe. Published on: 17 October Authors: E. Gropp, Daniel S. Published on: 16 October This paper describes a method for learning anomaly behavior in the video by finding an attention region from spatiotemporal information, in contrast to the full-frame learning.

In our proposed method, a robust With the advent of cloud-based parallel processing techniques, services such as MapReduce have been considered by many businesses and researchers for different applications of big data computation including ma Published on: 15 October Real-time information mining of a big dataset consisting of time series data is a very challenging task.

For this purpose, we propose using the mean distance and the standard deviation to enhance the accuracy Published on: 13 October This study deals with the problem of rea-time obtaining quality data on the road traffic parameters based on the static street video surveillance camera data. The existing road traffic monitoring solutions are Published on: 6 October In the past decades, the rapid growth of computer and database technologies has led to the rapid growth of large-scale datasets.

On the other hand, data mining applications with high dimensional datasets that Published on: 2 October Extensive usage of Internet based applications in day to day life has led to generation of huge amounts of data every minute. Apart from humans, data is generated by machines like sensors, satellite, CCTV etc Authors: Gousiya Begum, S.

Zahoor Ul Huq and A. Siva Kumar. Published on: 30 September The growing number of Internet of Things IoT devices provide a massive pool of sensing data.

However, turning data into actionable insights is not a trivial task, especially in the context of IoT, where appl Authors: Tanmaya Mahapatra. Published on: 29 September In this age, information technology has grown significantly.

Computer networks, which connect a device to others, have made it easier for people to transfer data than before. Moreover, smart devices have the c

Machine Learning Models and Algorithms for Big Data Classification

Note that while every book here is provided for free, consider purchasing the hard copy if you find any particularly helpful. In many cases you will find Amazon links to the printed version, but bear in mind that these are affiliate links, and purchasing through them will help support not only the authors of these books, but also LearnDataSci. Thank you for reading, and thank you in advance for helping support this website. Comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. Saidulu Published Computer Science. Today, as we are observing, massive sized and complex structured data is becoming available from variety of diverse sources, organizations are making attempt to utilize these plentiful resources for the purpose of enhance innovation, increase decisional and operational efficiency. Machine learning is a kind of artificial intelligence method to discover knowledge for making intelligent decisions.

Big Data and Machine Learning in Quantitative Investment [1ed.]1119522196, 978-1119522195

Data mining. With big data analytics comes big insights into profitability. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Big data is big business.

Outpatients who fail to attend their appointments have a negative impact on the healthcare outcome. Thus, healthcare organizations facing new opportunities, one of them is to improve the quality of healthcare Citation: Journal of Big Data 7

This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree a hierarchical approach , random forest an ensemble hierarchical approach , and deep learning a layered approach are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs Matlab and R presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field.

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Introducing Data Science [PDF]

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PDF | This paper discusses the role of Machine Learning (ML) based algorithms and methods in Big Data Processing & Analytics (BDA). ML and BDA are both.


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PDF | Machine learning is an artificial intelligence method of discovering knowledge for making intelligent decisions. Big Data has great.

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