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By surpassing the baseline performance, we believe that our work can be a stepping stone for deep learning implementation in argumentation mining field.
Deep Learning Implementers Speak!
Lehman, C. D. et al. Mammographic breast density assessment using deep learning: clinical implementation.
We implement DLBH to learn deep learning hashing for mobile location recognition in two main steps.
Although we are not aware of any successful implementations, the potential of deep learning for interpreting big data has been explored.56 Multiple deep learning architectures were evaluated for suitability to handle the challenges of big data analytics, including volume of data, speed of processing and low data quality.
One implementation of deep learning comes in the form of feedforward neural networks, where levels of abstraction are modeled by multiple non-linear hidden layers.
Schnet a deep learning architecture for molecules and materials.
What IBM is promising is the most efficient distributed deep learning library for breaking up a giant deep learning problem into hundreds of smaller deep learning problems.
WeLink: Deep learning platform for identifying threats on social media.
Want to take your Deep Learning skills from proof-of-concept implementations to what's needed for real-world deployment, monitoring, continuous improvement, etc? Check out Full Stack Deep Learning Bootcamp, co-organized with Josh Tobin, Sergey Karayev.
Shuhui Bu et al. for the first time applied deep learning for 3D shape retrieval [51].
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com