[arXiv] BigDataFr recommends: Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction

BigDataFr recommends: Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction Subjects: Learning (cs.LG); Machine Learning (stat.ML) […] ABSTRACT Developing a Brain-Computer Interface~(BCI) for seizure prediction can help epileptic patients have a better quality of life. However, there are many difficulties and challenges in developing such a system as a real-life support for […]

[Datasciencecentral – Tips] BigDataFr recommends: Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics

BigDataFr recommends: Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics […] In this article, Vincent Granville clarifies the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics. As data science is […]

[arXiv] BigDataFr recommends: Distributed Real-Time Sentiment Analysis for Big Data Social Streams

BigDataFr recommends: Distributed Real-Time Sentiment Analysis for Big Data Social Streams […] ABSTRACT Big data trend has enforced the data-centric systems to have continuous fast data streams. In recent years, real-time analytics on stream data has formed into a new research field, which aims to answer queries about what-is-happening-now with a negligible delay. The real […]

[arXiv] BigDataFr recommends: Architecting Time-Critical Big-Data Systems

BigDataFr recommends: Architecting Time-Critical Big-Data Systems Subjects: Distributed, Parallel, and Cluster Computing (cs.DC) […] – Current infrastructures for developing big-data applications are able to process –via big-data analytics-huge amounts of data, using clusters of machines that collaborate to perform parallel computations. However, current infrastructures were not designed to work with the requirements of time-critical applications; […]

[arXiv] BigDataFr recommends: Big Data Analytics in Cloud environment using #Hadoop

BigDataFr recommends: Big Data Analytics in Cloud environment using Hadoop Subjects: Distributed, Parallel, and Cluster Computing (cs.DC) […] The Big Data management is a problem right now. The Big Data growth is very high. It is very difficult to manage due to various characteristics. This manuscript focuses on Big Data analytics in cloud environment using […]

[Datasciencecentral] BigDataFr recommends: Beyond Deep Learning – 3rd Generation Neural Nets

BigDataFr recommends: Beyond Deep Learning – 3rd Generation Neural Nets […] “By far the fastest expanding frontier of data science is AI and specifically the rapid advances in Deep Learning.  Advances in Deep Learning have been dependent on artificial neural nets and especially Convolutional Neural Nets (CNNs).  In fact our use of the word “deep” […]

[arXiv] BigDataFr recommends: Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data

BigDataFr recommends: Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data Subjects: Databases (cs.DB) […] This research explores the potential to analyze bank card payments and ATM cash withdrawals in order to map and quantify how people are impacted by and recover from natural disasters. Our approach defines a disaster-affected community’s economic recovery time […]