Dramatically improving currency trading models with AI using Keras Deep Learning and PivotBillions. As has become more and more apparent in this day and age, data is scal...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
P-values are used in statistics and scientific publications, much less so in machine learning applications where re-sampling techniques are favored and easy to implement ...
In many fields of science, it is important to understand the relevance of new theories or hypotheses in a description of experimental data, assuming that such data are al...
As the need for advanced analytics increases in organizations, enterprises large and small struggle to find and sustain the professional resources they need to meet their...
The blockchain is one of the hottest and fastest growing skills in the IT sector today. It is said that there are around 44% of organizations that have adopted blockchain...
Since the (non) listed abstract submissions for this year’s conference are presumably from Academia, any preferences for related conferences more accessible and rel...
Summary: Recurrent Neural Nets (RNNs) are at the core of the most common AI applications in use today but we are rapidly recognizing broad time series problem types where...
The last decade has seen unprecedented advancements in artificial intelligence. We have moved towards a data-centric approach, and data is the center of everything digita...