记录笔记的方式应该根据个人的喜好和习惯来决定,因为不同的人有不同的偏好和需要。重要的是确保记录下来的信息准确无误,易于理解,并且方便日后查阅和复习。我曾经热衷于记录完善的电子笔记,但逐渐发现这种做法效率不高。因此,在大部分情况下,我会采用在源文件基础上添加笔记的方式。这可以减少时间和精力的浪费,并且让我更专注于学习和实践。今后我将在博客中分享的更多内容。
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├── Machine Learning and Deep Learning
│ ├── Adversarial Attack
│ ├── Anomaly Detection
│ ├── Deep Learning
│ ├── Explainable Machine Learning
│ ├── Flow-based Generative Model
│ ├── Generative Adversarial Network
│ ├── Life-long Learning
│ ├── Machine Learning
│ ├── Meta Learning
│ ├── Network Compression
│ ├── Reinforcement Learning
│ ├── Semi-supervised Learning
│ ├── Seq2Seq
│ ├── Structured Learning
│ ├── Transfer Learning
│ └── Unsupervised Learning
├── The Verilog Hardware Description Language
├── 编码
├── 电子信息系统
└── 软件工程导论