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Probing the evolution of fault properties during the seismic cycle with deep learning

Flipboard

We use seismic waves that pass through the hypocentral region of the 2016 M6.5 Norcia earthquake together with Deep Learning (DL) to distinguish between foreshocks, aftershocks and time-to-failure (TTF). Artificial Intelligence technique based on Deep Learning is used to differentiate seismic waves before and after a M6.5

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Can Using Deep Learning to Write Code Help Software Developers Stand Out?

Smart Data Collective

Although there are plenty of tech jobs out there at the moment thanks to the tech talent gap and the Great Resignation, for people who want to secure competitive packages and accelerate their software development career with sought-after java jobs , a knowledge of deep learning or AI could help you to stand out from the rest.

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TensorFlow vs. PyTorch: What’s Better for a Deep Learning Project?

Towards AI

Photo by Marius Masalar on Unsplash Deep learning. A subset of machine learning utilizing multilayered neural networks, otherwise known as deep neural networks. If you’re getting started with deep learning, you’ll find yourself overwhelmed with the amount of frameworks. Let’s answer that question.

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Groq sparks LPU vs GPU face-off

Dataconomy

Recall the historic Go match in 2016 , where AlphaGo defeated the world champion Lee Sedol ? This attribute is particularly beneficial for algorithms that thrive on parallelization, effectively accelerating tasks that range from complex simulations to deep learning model training.

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Identification of Hazardous Areas for Priority Landmine Clearance: AI for Humanitarian Mine Action

ML @ CMU

For the Risk Modeling component, we designed a novel interpretable deep learning tabular model extending TabNet. Formally, we use the risk scores (r_i) estimated by our trained deep learning model to compute proxies for the benefit of demining candidate grid cell (i) with centroid ((x_i,y_i)).

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Top 10 Deep Learning Platforms in 2024

DagsHub

Source: Author Introduction Deep learning, a branch of machine learning inspired by biological neural networks, has become a key technique in artificial intelligence (AI) applications. Deep learning methods use multi-layer artificial neural networks to extract intricate patterns from large data sets.

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Entity Recognition with LLM: A Complete Evaluation

Towards AI

SpaCy is a language processing library written in Python and Cython that has been well-established since 2016. The majority of processing is a combination of deep learning, Transformers technologies (since version 3.0), and statistical analysis.