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 […]
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[Datasciencecentral] BigDataFr recommends: A Robot Took My Job – Was It a Robot or AI?
BigDataFr recommends: A Robot Took My Job – Was It a Robot or AI? […] There’s been a lot of contradictory opinion in the press recently about future job loss from robotics and AI. They range from Bill Gates’ hand wringing assertion that we should slow this down by taxing robots to Treasury Secretary Steve […]
[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 […]
[Datasciencecentral] BigDataFr recommends: The Future Is Intelligent Apps
BigDataFr recommends: The Future Is Intelligent Apps […] I have seen the future! Of course, I seem to say that every other month (maybe that’s because the future keeps changing?), but this is a good one. The future is a collision between big data (and data science) and application development that will yield a world […]
[arXiv] BigDataFr recommends: Big Data for Social Sciences: Measuring patterns of human behavior through large-scale mobile phone data
BigDataFr recommends: Big Data for Social Sciences: Measuring patterns of human behavior through large-scale mobile phone data Subjects: Computers and Society (cs.CY); Social and Information Networks (cs.SI) […] ABSTRACT Through seven publications this dissertation shows how anonymized mobile phone data can contribute to the social good and provide insights into human behaviour on a large […]
[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] BigDataFr recommends: The Mathematics of Machine Learning
BigDataFr recommends: The Mathematics of Machine Learning […] In the last few months, I have had several people contact me about their enthusiasm for venturing into the world of data science and using Machine Learning (ML) techniques to probe statistical regularities and build impeccable data-driven products. However, I’ve observed that some actually lack the necessary mathematical […]
[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 […]