이 첫 번째 구현은 신경망의 진화에 대해 필자는 그라데이션 하강 알고리즘. 모두 단일 계층 퍼셉트론의 가장 간단한 네트워크와 함께 시작 및 다른 아키텍처를 통해 작동 되며 자연 언어 처리 및 훨씬 더. 처리 이어질 것입니다 결국 네트워크 주식 시장 가격의 움직임을 예측할 수 있는, 얼굴 인식을 수행 하는 방법을 학습-이것은 내 첫 번째는 그라데이션 하강 알고리즘 구현의 내가 줘야 해(translate from):This my first implementation of gradient descent algorithm in which I will write about the evolution of neural networks. I will start with the most simple network of all, the Single Layer Perceptron, and work through different architectures and learning methods which will eventually lead to networks that can predict stock market price movements, perform face recognition, handle natural language processing and much more.-This is my first implementation of gradient descent algorithm in which I will write about the evolution of neural networks. I will start with the most simple network of all, the Single Layer Perceptron, and work through different architectures and learning methods which will eventually lead to networks that can predict stock market price movements, perform face recognition, handle natural language processing and much more.




File list:
myGradientDescent
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................\.................\myGradientDescent.csproj
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................\myGradientDescent.sln
................\myGradientDescent.suo