BigDataFr recommends: Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models […] With the tremendous increase in the amount of biological literature, developing automated methods for extracting big data from papers, building models and explaining big mechanisms becomes a necessity. We describe here our approach to translating machine reading outputs, obtained by […]
Innovation
[arXiv] BigDataFr recommends: Big Data, Data Science, and Civil Rights
BigDataFr recommends: Big Data, Data Science, and Civil Rights […] Advances in data analytics bring with them civil rights implications. Data-driven and algorithmic decision making increasingly determine how businesses target advertisements to consumers, how police departments monitor individuals or groups, how banks decide who gets a loan and who does not, how employers hire, how […]
[Analyticbridge] BigDataFr recommends: The Most Important Lessons Learned from Data Science Projects
BigDataFr recommends: The Most Important Lessons Learned from Data Science Projects […] An overwhelming expansion of data archives posed a challenge to various industries, as these are now struggling to make use of such enormous amount of information. Almost 90% of all data ever recorded worldwide has been created in the last decade alone. This […]
[arXiv] BigDataFr recommends: Forecasting in the light of Big Data
BigDataFr recommends: When Will AI Exceed Human Performance? Evidence from AI Experts […] Predicting the future state of a system has always been a natural motivation for science and practical applications. Such a topic, beyond its obvious technical and societal relevance, is also interesting from a conceptual point of view. This owes to the fact […]
[arXiv] BigDataFr recommends: When Will AI Exceed Human Performance? Evidence from AI Experts
BigDataFr recommends: When Will AI Exceed Human Performance? Evidence from AI Experts […] Advances in artificial intelligence (AI) will transform modern life by reshaping transportation, health, science, finance, and the military. To adapt public policy, we need to better anticipate these advances. Here we report the results from a large survey of machine learning researchers […]
[ArXiv] BigDataFr recommends: Data Visualization on Day One: Bringing Big Ideas into Intro Stats Early and Often
BigDataFr recommends: A Proposed Architecture for Big Data Driven Supply Chain Analytics […] In a world awash with data, the ability to think and compute with data has become an important skill for students in many fields. For that reason, inclusion of some level of statistical computing in many introductory-level courses has grown more common […]
[ArXiv] BigDataFr recommends: A Proposed Architecture for Big Data Driven Supply Chain Analytics
BigDataFr recommends: A Proposed Architecture for Big Data Driven Supply Chain Analytics […] Advancement in information and communication technology (ICT) has given rise to explosion of data in every field of operations. Working with the enormous volume of data (or Big Data, as it is popularly known as) for extraction of useful information to support […]
[ArXiv] BigDataFr recommends: Big Data Analysis Using Shrinkage Strategies
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 […]
[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 […]