machine learning platform
Machine learning platforms are for new technologist. Developers need to know how and when to harness their power. Working within the ML landscape while using the right tools can make it easier for developers to create a productive algorithm that taps into its power. machine learning platforms and tools are available now as resources to seamlessly integrate the power of ML into daily tasks.
Jubatus: An open source platform for distributed online machine learning
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Distributed computing is essential for handling very large datasets. Online learning is also promising for learning from rapid data streams. However, it is still an unresolved problem how to combine them for scalable learning and prediction on big data streams. We propose
Cometcloudcare (c3). distributed machine learning platform -as-a-service with privacy preservation
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The growth of data sharing initiatives in neuroscience and genomics [1 1 1 25] represents an exciting opportunity to confront the small N problem plaguing contemporary studies [20]. When possible, open data sharing provides the greatest benefit. However some
Ml. lib: robust, cross- platform , open-source machine learning for max and pure data.
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This paper documents the development of ml. lib: a set of opensource tools designed for employing a wide range of machine learning techniques within two popular real-time programming environments, namely Max and Pure Data. ml. lib is a crossplatform
ASAP: a hybrid computer platform using machine learning and solar imaging for automated prediction of solar flares
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The importance of real-time processing of solar data especially for space weather 8 applications is increasing continuously. In this paper, we present an automated hybrid 9 computer platform for the short-term prediction of significant solar flares using SOHO/MDI 10
OpenML: An R package to connect to the networked machine learning platform OpenML
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OpenML is an online machine learning platform where researchers can easily share data, machine learning tasks and experiments as well as organize them online to work and collaborate more efficiently. In this paper, we present an R package to interface with the
Investigating cross- platform robustness in machine learning based idss for 802.11 networks
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Security and Intrusion detection in 802.11 networks is currently an active area of research where WiFi specific Data Link layer attacks are an area of focus. While these attacks are very simple in implementation, their effect on WiFi networks can be devastating. Recent research
Integrating machine learning in a semantic web platform for traffic forecasting and routing
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Semantic Web technologies proved to be successful in integrating and interlinking data. However, traditional processing operations offered by Semantic Web technologies are limited to conceptual query answering. Growing the size of datasets, typical operations from
A construction method of gene expression data based on information gain and extreme learning machine classifier on cloud platform
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With the large-scale application of high dimensional gene expression data which exists lots of redundant information, it waste a lot of time in feature selection and classification. By analyzing the process of MapReduce computing paradigms on cloud platform , it is found
Thoth: Automatic Resource Management with Machine Learning for Container-based Cloud Platform .
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Platform -as-a-Service (PaaS) providers often encounter fluctuation in computing resource usage due to workload changes, resulting in performance degradation. To maintain acceptable service quality, providers need to manually adjust resource allocation
OpenML: a networked science platform for machine learning
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OpenML is an online machine learning platform where researchers can automatically log and share data, code, and experiments in fine detail and organize them online to work and collaborate more effectively (Vanschoren et al.). It is designed to create a networked
An Event Search Platform Using Machine Learning .
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Currently, the evolution of technology allows to find which events occurs around us at any given location. Social networks are one of the reasons of this trend and new applications are emerging aiming at finding and disclosing events. This paper proposes a platform of event
Machine Learning Powered Data Platform for High-Quality Speech and NLP Workflows.
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Abstract Machine learning (ML) models-like deep neural networksrequire substantial amounts of training data. Also, the training dataset should be properly annotated to obtain satisfactory results. This paper describes a platform designed to create high-quality datasets
Review rating-based platform screening and new complementor entry: Evidence from natural experiment and machine learning of a sharing economy
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Platform owners often strive to reduce adverse selection and increase quality reputation by redesigning their platforms. One such platform design is to screen incumbent complementors by ranking them based on their review ratings. We theorize that this rating
Optimized framework for e- learning platform using machine intense learning algorithm
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When we hear or mention the word education it will bring the vivid image of organized class rooms having strict lectures and doodling students in our thought. But technology has been revolutionized and it also changing the education system also. E- learning is one of the main
ArchMLP: Machine Learning Platform
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ABSTRACT As Machine Learning research continues to expand, the tools available to practitioners grow in sophistication, abstracting away the rigorous implementation details that often define the development of complex mathematical models. While powerful, many of
Onelearn: A Unified and Distributed Machine Learning Platform with High Performance
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Software frameworks for machine learning play key roles in the design and development of machine learning applications. However, more and more complicated models are developed and data volume becomes very huge, therefor distributed training is necessary
TFX Frontend: A Graphical User Interface for a Production-Scale Machine Learning Platform
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The widespread use of machine learning has highlighted the need for platforms that provide integrated tools for all phases of the machine learning development process. An end-to-end machine learning platform contains components that span from ingesting raw data to serving
Conceptualization of an Autonomic Machine Learning Platform for Non-Expert Developers
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Machine learning is an approach to develop some algorithm for problem solving from data of the problem domain without coding programs. Although there are various machine learning tools with which machine learning applications can be developed relatively easily, non
Implementation of BM25 on Husky A Distributed Machine Learning Platform
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In 21st Century, big data processing and analyzing is a hot topic and having an efficient and expressive data computing system is very important. Hadoop and Spark are some widely used systems for massive data processing and they are easy to use. However, the over
IDEPI: rapid prediction of HIV-1 antibody epitopes and other phenotypic features from labeled genetic sequence data using a flexible machine learning platform .
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Since its identification in 198 HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals a cure and a vaccine remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic