… First, for end users of deep learning software tools, our benchmarking results can serve as a
… platforms and software tools. Second, for developers of deep learning software tools, our in-…

… a broad set of tools and techniques in the efficient deep learning landscape. In this
section, we present a practical guide for practitioners to use, and how these tools and techniques …

… paper we introduce ‘deep learning’ as a technique to improve the objectivity and efficiency
of … We conclude that ‘deep learning’ holds great promise to improve the efficacy of prostate …

… learning models are initially presented, while we also provide a comprehensive overview of
the recent deep learning … current gRNA design tools with a focus on the deep learning ones. …

… which the algorithm learns, deep learning approaches learn the important features as well as
… tools that are available to aid in the construction and efficient execution of deep learning as …

… that can be addressed by Deep Learning. We will present some studies in Deep Learning
that are used as a solution for data analysis. Finally, some Deep Learning challenges due to …

… Autoencoders [66] are NNs that are used to learn efficient encodings (ie, compressed
representations) that extract significant features from the training data. Their architecture consists …

… to deep learning programs. Then we evaluate the performance of some popular deep learning
tools … noticeable drawbacks while running those deep learning tools. So encapsulating …

… of deep learning techniques in NLP, with a focus on the various tasks where deep learning
is … Finally, we emphasize the main limits of deep learning in NLP and current research …

… Other applications of deep learning to FWI The deep learning approach to FWI I describe …
using deep learning software and using several concepts popular in deep learning. There are …