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lancecarlson.com
| | www.honeybadger.io
2.8 parsecs away

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| | Unlock the power of background processing in Ruby with Sidekiq. Learn how to create, schedule, and manage background jobs with and without ActiveJob
| | abuisman.com
3.5 parsecs away

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| | Blog about solving problems with code, mostly Ruby, and other things I have learned working as an engineer and a technical leader
| | electric-sql.com
2.9 parsecs away

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| | Local AI with Postgres, pgvector and llama2, running inside a Tauri app with realtime sync powered by ElectricSQL ?? This is the architecture of the future!
| | neuralnetworksanddeeplearning.com
13.4 parsecs away

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| [AI summary] The text provides an in-depth explanation of the backpropagation algorithm in neural networks. It starts by discussing the concept of how small changes in weights propagate through the network to affect the final cost, leading to the derivation of the partial derivatives required for gradient descent. The explanation includes a heuristic argument based on tracking the perturbation of weights through the network, resulting in a chain of partial derivatives. The text also touches on the historical context of how backpropagation was discovered, emphasizing the process of simplifying complex proofs and the role of using weighted inputs (z-values) as intermediate variables to streamline the derivation. Finally, it concludes with a citation and licens...