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【深度学习笔记】第 4 课:模型性能评估 - CusterFun - 博客园
【深度学习笔记】第 4 课:模型性能评估 - CusterFun - 博客园
training set 训练集 validation set 验证集 test set测试集 这些与衡量你做的怎么样有关 当你知道怎么衡量你在一个问题的表现,问题就解决了一半。(衡量表现的重要性) 每个你将建立的分类器都会尝试记住训练集,并且它通常在这方面会做的很好很好 你的工作 是帮助它泛化到新
·cnblogs.com·
【深度学习笔记】第 4 课:模型性能评估 - CusterFun - 博客园
Rcell的个人空间_哔哩哔哩_bilibili
Rcell的个人空间_哔哩哔哩_bilibili
Rcell,,,bilibili是国内知名的视频弹幕网站,这里有及时的动漫新番,活跃的ACG氛围,有创意的Up主。大家可以在这里找到许多欢乐。
·space.bilibili.com·
Rcell的个人空间_哔哩哔哩_bilibili
Stripe
Stripe
Stripe has 64 repositories available. Follow their code on GitHub.
·github.com·
Stripe
去问AI
去问AI
去问AI, 写作, 聊天, 画图, ChatGPT, GPT-3.5, GPT-4, GPT4, GPT3.5, 免费好用的ChatGPT, ChatGPT直连站, ChatGPT免代理
·quwenai.com·
去问AI
RipX DeepRemix
RipX DeepRemix
“For remix projects and stem unmixing, the best is now even better.“Sound On Sound - April 2023 Almost all functionality within RipX is provided through
·hitnmix.com·
RipX DeepRemix
labmlai/annotated_deep_learning_paper_implementations: 🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
labmlai/annotated_deep_learning_paper_implementations: 🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cycleg...
·github.com·
labmlai/annotated_deep_learning_paper_implementations: 🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠