{"provider_name":"Hatena Blog","width":"100%","blog_url":"https://upura.hatenablog.com/","author_name":"upura","categories":["python","\u81ea\u7136\u8a00\u8a9e\u51e6\u7406"],"url":"https://upura.hatenablog.com/entry/2023/11/05/210818","image_url":null,"title":"\u8a00\u8a9e\u51e6\u7406100\u672c\u30ce\u30c3\u30af 2020\u300c74. \u6b63\u89e3\u7387\u306e\u8a08\u6e2c\u300d","description":"\u554f\u984c\u6587 nlp100.github.io \u554f\u984c\u306e\u6982\u8981 \u6b63\u89e3\u7387\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002 import joblib import numpy as np import torch from torch import nn, optim X_train = joblib.load('ch08/X_train.joblib') y_train = joblib.load('ch08/y_train.joblib') X_train = torch.from_numpy(X_train.astype(np.float32)).clone() y_train = torch.from_numpy(y_train.\u2026","height":"190","author_url":"https://blog.hatena.ne.jp/upura/","type":"rich","version":"1.0","blog_title":"u++\u306e\u5099\u5fd8\u9332","published":"2023-11-05 21:08:18","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fupura.hatenablog.com%2Fentry%2F2023%2F11%2F05%2F210818\" title=\"\u8a00\u8a9e\u51e6\u7406100\u672c\u30ce\u30c3\u30af 2020\u300c74. \u6b63\u89e3\u7387\u306e\u8a08\u6e2c\u300d - u++\u306e\u5099\u5fd8\u9332\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","provider_url":"https://hatena.blog"}