Guanin工人智慧Review: An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleIntroduction to Vision TransformerAug 29, 2022Aug 29, 2022
Guanin工人智慧Notes of Clean Code from Uncle Bob這是一篇不完整的 Clean Code — Uncle Bob 速記，內文請與影片搭配使用。Dec 31, 2021Dec 31, 2021
Guanin工人智慧Speed up Python numerical computation 660,000 times with NumbaPython 在現代科學運算上扮演很重要的角色，尤其是 Machine Learning 領域，其核心是一連串的矩陣運算和最佳化理論；但受限於其 Interpreter GIL 和 動態類型語言等等，在中大型運算上的效能一直為人所詬病，所以 Numpy 應運而生，大部分使用 C…Aug 30, 2021Aug 30, 2021
Guanin工人智慧Review: Meta Pseudo Labels — Series 3 of 3這是 Google Self-training 系列的最後一篇，這個系列第一篇提出了一個新的Teacher-student 的訓練架構：加入適當的噪聲後，在不斷的迭代訓練下，能夠不斷的推昇準確度。Jun 23, 20211Jun 23, 20211
Guanin工人智慧Review: Rethinking Pre-training and Self-training — Series 2 of 3Pre-training 一直是 Computer Vision 愛用的技術，一般認為它能夠非常快的配適在不同資料集（以及任務）上，早年甚至認為它在任何條件下都能夠快速的達到與 train-from-scratch 相等的準確度，甚至認為在相同的 iteration…Feb 27, 20211Feb 27, 20211
Guanin工人智慧Review: Self-training with Noisy Student improves ImageNet classification — Series 1 of 3Introduction to noisy studentFeb 15, 2021Feb 15, 2021
Guanin工人智慧How does Batch Normalization REALLY Work?(It's not about Internal Variate Shift)How Does Batch Normalization Help Optimization?Nov 16, 2020Nov 16, 2020
Guanin工人智慧Review: Attention is all you needIntroduction to Self-Attention and TransformerOct 9, 20201Oct 9, 20201
Guanin工人智慧Review a series of Semi-Supervised Learning algorithms: MixMatch, ReMixMatch and FixMatchIntroduction to Semi-SupervisedJul 7, 20201Jul 7, 20201
