NumPy(short forNumerical Python) is an open-source Python library fundamental for scientific computing. It supports a variety of high-level mathematical functions and is broadly used in data science, machine learning, and big data applications. With NumPy, you will be able to efficiently perform l...
Machine Learning engineering is the domain of software engineers and involves writing and testing code in a number of languages. A programmer who is accustomed to relational databases, Java, C++, and Python, but prefers not getting involved with Calculus, should probably consider this career trajecto...
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Physics-informed neural networks (PINNs) have recently become a viable modelling method for the scientific machine-learning community. The appeal of this network architecture lies in the coupling of a deep neural network (DNN) with partial differential equations (PDEs): the DNN can be considered a...
The features of the use of neural networks and machine learning methods for the design of food systems are studied using the example of processed cheese. A database has been developed that includes 869 cheese recipes, and a program for managing an electronic recipe directory. A neural network ...
We utilize a combination of machine-learning and related methods to increase the number of observed events by almost one order of magnitude. We determine the locations of the events using modern, high-precision methods and use these locations with a customized, calibrated local magnitude scale for...
2014). As in our approach, the technique operates in a black-box manner; it combines image processing for inconsistency detection with machine learning for improving accuracy. However, in addition to the different domain, Browserbite is evaluated on only 140 websites, which does not raise the ...
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Paper tables with annotated results for Studying the Impact of TensorFlow and PyTorch Bindings on Machine Learning Software Quality