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360digitmg.com | ||
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scorpil.com
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| | | | | In Part One of the "Understanding Generative AI" series, we delved into Tokenization - the process of dividing text into tokens, which serve as the fundamental units of information for neural networks. These tokens are crucial in shaping how AI interprets and processes language. Building upon this foundational knowledge, we are now ready to explore Neural Networks - the cornerstone technology underpinning all Artificial Intelligence research. A Short Look into the History Neural Networks, as a technology, have their roots in the 1940s and 1950s. | |
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www.asimovinstitute.org
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| | | | | With new neural networkarchitectures popping up every now and then, its hard to keep track of them all. Knowing all the abbreviations being thrown around (DCIGN, BiLSTM, DCGAN, anyone?) can be a bit overwhelming at first. So I decided to compose a cheat sheet containingmany of thosearchitectures. Most of theseare neural networks, some are completely [] | |
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codeincomplete.com
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| | | | | Personal Website for Jake Gordon | |
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www.analyticsvidhya.com
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| | | ProGAN is an extension of the training process of GAN that allows the generator models to train with stability in python | ||
