BigDataFr recommends: Big Data Analysis Using Shrinkage Strategies […] In this paper, we apply shrinkage strategies to estimate regression coefficients efficiently for the high-dimensional multiple regression model, where the number of samples is smaller than the number of predictors. We assume in the sparse linear model some of the predictors have very weak influence on […]
Innovation
[ArXiv] BigDataFr recommends: Best Practices for Applying Deep Learning to Novel Applications
BigDataFr recommends: Best Practices for Applying Deep Learning to Novel Applications […] This report is targeted to groups who are subject matter experts in their application but deep learning novices. It contains practical advice for those interested in testing the use of deep neural networks on applications that are novel for deep learning. We suggest […]
[ArXiv] BigDataFr recommends: Enabling Smart Data: Noise filtering in Big Data classification
BigDataFr recommends: Enabling Smart Data: Noise filtering in Big Data classification […] In any knowledge discovery process the value of extracted knowledge is directly related to the quality of the data used. Big Data problems, generated by massive growth in the scale of data observed in recent years, also follow the same dictate. A common […]
[arXiv] BigDataFr recommends: Big Data in HEP: A comprehensive use case study
BigDataFr recommends: Big Data in HEP: A comprehensive use case study […] Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems collectively called Big Data […]
[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 […]
[Datasciencecentra] BigDataFr recommends: How to Ensure Your CRM Data Is Fit For Purpose
BigDataFr recommends: How to Ensure Your CRM Data Is Fit For Purpose […] In this post we provide you with seven ways you can improve the quality of your data and ensure it is fit for purpose. Constantly improving upon the quality of your data is essential to remain ahead of your competition. Failure to keep […]
[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; […]
[Datasciencecentral – Tips] BigDataFr recommends: Data Integration Tools – Market Study
BigDataFr recommends: Data Integration Tools – Market Study […] This post is a brief review of leading Data Integration tools in the market. Heavily referencing from the Gartner 2016 report and peer reviews from my circle The Market The data integration tool market was worth approximately $2.8 billion at the end of 2015, an increase […]