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Transfer Learning in Computer VisionĀ 

insideBIGDATA

In this contributed article, Ihar Rubanau, Senior Software Developer at Sigma Software Group, discusses how transfer learning has become a popular technique in computer vision, allowing deep neural networks to be trained with limited data by leveraging pre-trained models.

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Field Boundaries Detection and Land Cover Classification And How EOSDA Does It

Data Science Dojo

The intricate mosaic of forests, agricultural lands, urban areas, water bodies, and other terrestrial features form the planet’s land cover. However, land use classification requires maps of field boundaries, potentially covering large areas containing thousands of farms. It takes work to obtain such a map.

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NTT Research Brings Innovation To Networking And Security

MoorInsights for Forbes

NTT Research, based in Silicon Valley, is pursuing potentially groundbreaking research in vital areas including all-optical networking and enhanced data security.

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Python libraries for generative AIĀ 

Data Science Dojo

TensorFlow provides a wide range of tools and resources for building and training generative models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Jax: Jax is a high-performance numerical computation library for Python with a focus on machine learning and deep learning research.

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Top data science conferences you must attend in 2023

Data Science Dojo

AAAI Conference on Artificial Intelligence ā€“ Washington DC, United States The AAAI Conference on Artificial Intelligence (AAAI) is a leading conference in the field of artificial intelligence research. It also includes tutorials, workshops, and invited talks by leading experts in the field.

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Research consultant explained: Roles, qualifications, career path

Dataconomy

Research consultants are experts in many fields. They research on behalf of their clients. They can interview experts in the industry, research their competitors, and analyze trends. What is a research consultant? It also outlines the steps to becoming one.

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Deep double descent ā€“ where data can damage performance

Data Science Dojo

It is a modern phenomenon in deep neural networks that presents its performance as a function of model complexity. Hence, a neural network’s performance experiences a second descent with increasing data complexity. It can be visualized with a shrunken area under the curve that also shifts towards the right.