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...In July 2023, work on the second edition was announced, which expands the project with updated content, new problems inspired by recent big-tech interviews, and introductions to modern machinelearning techniques such as XGBoost, CNNs, RNNs, and LSTMs. This collection serves both as a historical record of algorithm problem-solving and as a living resource for programmers preparing for interviews.
The library enables to create perceptrons with desired number of inputs and customized train rate. It enables to train the perceptrons according to the user input.
Check the Wiki page for usage examples and API
Este proyecto constituye una adaptacion y mejora del codigo ANFIS de dominio público de Roger Jang. / This project is an adaptation and improvement of the original public domain ANFIS code of Roger Jang.
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