{"blog_title":"HTN20190109\u306e\u65e5\u8a18","published":"2026-10-24 17:45:02","provider_url":"https://hatena.blog","categories":["DL"],"version":"1.0","image_url":null,"width":"100%","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fhtn20190109.hatenablog.com%2Fentry%2F2026%2F10%2F24%2F174502\" title=\"GRU\u306e\u5b9f\u88c5 - HTN20190109\u306e\u65e5\u8a18\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","title":"GRU\u306e\u5b9f\u88c5","author_name":"HTN20190109","url":"https://htn20190109.hatenablog.com/entry/2026/10/24/174502","author_url":"https://blog.hatena.ne.jp/HTN20190109/","description":"import numpy as npimport matplotlib.pyplot as plt np.random.seed(0) # -----------------------------# 1 activation# ----------------------------- def sigmoid(x): return 1.0 / ( 1.0 + np.exp(-x) ) def sigmoid_grad(y): return y * ( 1.0 - y ) def tanh_grad(y): return 1.0 - y**2 # -----------------------\u2026","type":"rich","provider_name":"Hatena Blog","height":"190","blog_url":"https://htn20190109.hatenablog.com/"}