BigDataFr recommends: A Big Data Analysis Framework Using Apache Spark and Deep Learning […] Subjects: Databases (cs.DB); Learning (cs.LG); Machine Learning (stat.ML) With the spreading prevalence of Big Data, many advances have recently been made in this field. Frameworks such as Apache Hadoop and Apache Spark have gained a lot of traction over the past […]

BigDataFr recommends: High Precision Computing: Benchmark, Examples, and Tutorial […] In some applications, using the standard precision in your programming language of choice, may not be enough, and can lead to disastrous errors. In some cases, you work with a library that is supposed to provide very high precision, when in fact the library in […]

BigDataFr recommends: Learning to Predict with Big Data […] Subjects: Big spatio-temporal datasets, available through both open and administrative data sources, offer significant potential for social science research. The magnitude of the data allows for increased resolution and analysis at individual level. One of the issues researchers face with such data is the stationarity assumption. […]

BigDataFr recommends: Quantitative Alienation in the Workplace […] For my graduate paper, I studied perceptions of workplace stress through the critical lens of social disablement. Writing this paper was certainly an intellectual exercise that at the time didn’t seem to have many practical applications. I am therefore honoured to become better acquainted with the “mechanics” […]

BigDataFr recommends: Collaborative Anomaly Detection Framework for handling Big Data of Cloud Computing […] Subjects: Cryptography and Security (cs.CR) With the ubiquitous computing of providing services and applications at anywhere and anytime, cloud computing is the best option as it offers flexible and pay-per-use based services to its customers. Nevertheless, security and privacy are the […]

BigDataFr recommends: Distributed Spatial Data Clustering as a New Approach for Big Data Analysis […] Subjects: Distributed, Parallel, and Cluster Computing (cs.DC) In this paper we propose a new approach for Big Data mining and analysis. This new approach works well on distributed datasets and deals with data clustering task of the analysis. The approach […]

BigDataFr recommends: How will Artificial Intelligence affect Your career? […] We have long been used to manual work being automated. We are finally at a juncture where even knowledge work is starting to see the same fate. Weren’t engineering, medicine and law supposed to be future-proof careers? For example, the world’s largest hedge fund Bridgewater […]

BigDataFr recommends: Communication Efficient Checking of Big Data Operations […] Subjects: Data Structures and Algorithms (cs.DS); Distributed, Parallel, and Cluster Computing (cs.DC) We propose fast probabilistic algorithms with low (i.e., sublinear in the input size) communication volume to check the correctness of operations in Big Data processing frameworks and distributed databases. Our checkers cover many […]

BigDataFr recommends: To PhD or not to PhD? […] …That is the question. Further study often seems the most appealing route to go down, and for many companies out there it’s often heralded as a must have for data science, but it isn’t always so and isn’t always pivotal in advancing your career. To Ph.D. […]

BigDataFr recommends: Big Data Analytics and Its Applications […] Subjects: Computers and Society (cs.CY) The term, Big Data, has been authored to refer to the extensive heave of data that can’t be managed by traditional data handling methods or techniques. The field of Big Data plays an indispensable role in various fields, such as agriculture, […]