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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[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 […]
[arXiv] BigDataFr recommends: Correct classification for big/smart/fast data machine learning
BigDataFr recommends: Correct classification for big/smart/fast data machine learning Subjects: Learning (cs.LG); Information Theory (cs.IT) […] Table (database) / Relational database Classification for big/smart/fast data machine learning is one of the most important tasks of predictive analytics and extracting valuable information from data. It is core applied technique for what now understood under data science […]
[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 […]
[arXiv] BigDataFr recommends : Big Data analytics. Three use cases with R, Python and #Spark #datascientist
BigDataFr recommends: Big Data analytics. Three use cases with R, Python and Spark Subjects: Applications (stat.AP); Learning (cs.LG) […] Management and analysis of big data are systematically associated with a data distributed architecture in the Hadoop and now Spark frameworks. This article offers an introduction for statisticians to these technologies by comparing the performance obtained […]
[arXiv] BigDataFr recommends: The Scalable Langevin Exact Algorithm: Bayesian Inference for Big Data
BigDataFr recommends: The Scalable Langevin Exact Algorithm: Bayesian Inference for Big Data Subjects: Methodology (stat.ME); Computation (stat.CO) […] This paper introduces a class of Monte Carlo algorithms which are based upon simulating a Markov process whose quasi-stationary distribution coincides with the distribution of interest. This differs fundamentally from, say, current Markov chain Monte Carlo in […]
[Datasciencecentral] BigDataFr recommends: Finding Career Opportunities in AI
BigDataFr recommends: Finding Career Opportunities in AI […] If you’re a data scientist thinking about expanding your career options into AI you’ve got a forest and trees problem. There’s a lot going on in deep learning and reinforcement learning but do these areas hold the best future job prospects or do we need to be […]
[arXiv] BigDataFr recommends: Human-Algorithm Interaction Biases in the Big Data Cycle: A Markov Chain Iterated Learning Framework
BigDataFr recommends: Human-Algorithm Interaction Biases in the Big Data Cycle: A Markov Chain Iterated Learning Framework Comments: This research was supported by National Science Foundation grant NSF-1549981 Subjects: Learning (cs.LG); Human-Computer Interaction (cs.HC) […] Early supervised machine learning algorithms have relied on reliable expert labels to build predictive models. However, the gates of data generation […]
[Datasciencecentral] BigDataFr recommends: 5 Free Statistics eBooks You Need to Read This Autumn
BigDataFr recommends: 5 Free Statistics eBooks You Need to Read This Autumn […] Did you have a good, relaxing break over the summer? Are you refreshed and re-energised, looking forward to a new start, a new you and brushing up on your data analysis skills? If so, I’ve thrown together a collection of a few […]
[Datasciencecentral] BigDataFr recommends: A methodology for solving problems with DataScience for Internet of Things – Full – #iot
BigDataFr recommends: A methodology for solving problems with DataScience for Internet of Things – Part 1 and 2 […] This two part blog is based on my forthcoming book: Data Science for Internet of Things. It is also the basis for the course I teach Data Science for Internet of Things Course. I will be […]