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bartoszmilewski.com | ||
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blog.jle.im
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| | | | | Weblog of Justin Le, covering various adventures in programming and explorations in the worlds of computation physics, and knowledge. | |
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kavita-ganesan.com
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| | | | | This article examines the parts that make up neural networks and deep neural networks, as well as the fundamental different types of models (e.g. regression), their constituent parts (and how they contribute to model accuracy), and which tasks they are designed to learn. | |
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thenumb.at
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| | | | | [AI summary] The text provides an in-depth overview of various neural field techniques, focusing on their applications in representing images, geometry, and light fields. It discusses methods such as positional encoding, hash encoding, and neural SDFs, highlighting their advantages in terms of model size, training efficiency, and quality of representation. The text also touches on the broader implications of these techniques in fields like computer vision and real-time rendering, emphasizing their potential to revolutionize how we model and interact with digital content. | |
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www.analyticsvidhya.com
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| | | Get to know large language models: learn how these models, trained on massive amounts of text data, can understand, analyze, and generate. | ||
