CMU 10-414/714: Deep Learning Systems
约 1308 字大约 4 分钟
2025-09-23
CMU 10-414/714: Deep Learning Systems - CS自学指南
【深度学习系统：算法与实现 10-714 2022】卡耐基梅隆—ai中英字幕
一门相似的课程 智能计算系统官方网站
- 智能计算系统 - CS自学指南
- 学哪个待定, 先看看introduction TODO:
- CMU 11-868: Large Language Model System - CS自学指南
prompt
我有一份英文课程 PPT。请根据 PPT 内容，翻译出一份完整的中文笔记，要求如下：
- 用 `markdown` 代码块输出
- 公式使用 LaTeX 语法（用 `$` 包裹, `$`符号和公式之间不要有空格）
- 笔记需要涵盖 PPT 的**所有**内容，包括概念、定理、例子、图表信息等, 如果需要插入截图, 请标注
- 每行末尾不需要加上`。`
- 结构清晰，适当使用标题（`#`）、代码块、内嵌latex公式等 Markdown 语法, 其中标题为# Lec6 xxx, ## 6.1, ## 6.2...Schedule
Homework Details
| Homework | Released | Due | Colab Link | GitHub Repo |
|---|---|---|---|---|
| Homework 0 | 8/29/24 | 9/12/24 | hw0 colab | hw0 github |
| Homework 1 | 9/10/24 | 9/24/24 | hw1 colab | hw1 github |
| Homework 2 | 9/24/24 | 10/10/24 | hw2 colab | hw2 github |
| Homework 3 | 10/10/24 | 10/31/24 | hw3 colab | hw3 github |
| Homework 4 | 10/31/24 | 11/16/24 | hw4 colab | hw4 github |
| Homework 4 Extra (714 only) | 10/31/24 | 11/16/24 | hw4 extra colab | hw4 extra github |
Lecture&Homework Schedule
| Date (CMU) | Lecture | Instructor | Slides | Video (2022 version) | Homework |
|---|---|---|---|---|---|
| 8/27 | 1 - Introduction / Logistics | Kolter | YouTube / Bilibili | ||
| 8/29 | 2 - ML Refresher / Softmax Regression | Kolter | YouTube / Bilibili | Homework 0 Released | |
| 9/3 | 3 - Manual Neural Networks / Backprop | Kolter | YouTube (pt 1) YouTube (pt 2) / Bilibili (pt 1) Bilibili (pt 2) | ||
| 9/5 | 4 - Automatic Differentiation | Chen | YouTube / Bilibili | ||
| 9/10 | 5 - Automatic Differentiation Implementation | Chen | ipynb | YouTube / Bilibili | Homework 1 Released |
| 9/12 | 6 - Optimization | Kolter | YouTube / Bilibili | Homework 0 Due | |
| 9/17 | 7 - Neural Network Library Abstractions | Chen | YouTube / Bilibili | ||
| 9/19 | 9 - Normalization, Dropout, + Implementation | Kolter | YouTube / Bilibili | ||
| 9/24 | 8 - NN Library Implementation | Chen | ipynb | YouTube / Bilibili | Homework 1 Due, Homework 2 Released |
| 9/26 | 10 - Convolutional Networks | Kolter | YouTube / Bilibili | ||
| 10/1 | 11 - Hardware Acceleration for Linear Algebra | Chen | YouTube / Bilibili | ||
| 10/3 | 12 - Hardware Acceleration + GPUs | Chen | YouTube / Bilibili | ||
| 10/8 | 13 - Hardware Acceleration Implementation | Chen | ipynb | YouTube / Bilibili | |
| 10/10 | 14 - Convoluations Network Implementation | Kolter | ipynb | YouTube / Bilibili | Homework 2 Due, Homework 3 Released |
| 10/15 | No class - Fall Break | ||||
| 10/17 | No class - Fall Break | ||||
| 10/22 | 15 - Sequence Modeling + RNNs | Kolter | YouTube / Bilibili | ||
| 10/24 | 16 - Sequence Modeling Implementation | Kolter | ipynb | YouTube / Bilibili | |
| 10/29 | 17 - Transformers and Autoregressive Models | Kolter | Youtube / Bilibili | ||
| 10/31 | 18 - Transformers Implementation | Kolter | ipynb | Youtube / Bilibili | Homework 3 Due, Homework 4 Released, Homework 4 Extra Released |
| 11/5 | No class - Democracy Day | ||||
| 11/7 | 19 - Training Large Models | Chen | YouTube / Bilibili | ||
| 11/12 | 20 - Generative Models | Chen | YouTube / Bilibili | ||
| 11/14 | 21 - Generative Models Implementation | Chen | ipynb | YouTube / Bilibili | |
| 11/16 | Homework 4 Due, Homework 4 Extra Due | ||||
| 11/19 | 22 - Customize Pretrained Models | Chen | |||
| 11/21 | 23 - Model Deployment | Chen | Youtube / Bilibili | ||
| 11/26 | 24 - Machine Learning Compilation and Deployment Implementation | Chen | ipynb | Youtube / Bilibili | |
| 11/28 | No class - Thanksgiving | ||||
| 12/3 | 25 - Future Directions / Q&A | Both | |||
| 12/5 | 26 - Student project presentations | Students |
Slides下载
AI真是太好用了XD
#!/bin/bash
# 创建一个目录来存放下载的幻灯片
OUTPUT_DIR="dlsys_course_slides"
mkdir -p "$OUTPUT_DIR"
echo "将在 '$OUTPUT_DIR/' 目录中保存所有文件"
echo "-----------------------------------------"
# 定义一个辅助函数来处理单个文件的下载，避免代码重复
download_file() {
local filename="$1"
local url="$2"
echo "正在下载: $filename"
# 使用 wget 命令
# -O 指定输出文件名 (包括目录)
# -q 使其静默运行，--show-progress 显示一个简洁的进度条
wget -q --show-progress -O "$OUTPUT_DIR/$filename" "$url"
if [ $? -eq 0 ]; then
echo "下载完成."
else
echo "下载失败: $filename"
fi
echo "" # 添加一个空行以提高可读性
}
# --- 所有 PDF 链接和对应的文件名都硬编码在此 ---
download_file "1 - Introduction - Logistics.pdf" "https://dlsyscourse.org/slides/intro.pdf"
download_file "2 - ML Refresher - Softmax Regression.pdf" "https://dlsyscourse.org/slides/2-softmax_regression.pdf"
download_file "3 - Manual Neural Networks - Backprop.pdf" "https://dlsyscourse.org/slides/manual_neural_nets.pdf"
download_file "4 - Automatic Differentiation.pdf" "https://dlsyscourse.org/slides/4-automatic-differentiation.pdf"
download_file "6 - Optimization.pdf" "https://dlsyscourse.org/slides/fc_init_opt.pdf"
download_file "7 - Neural Network Library Abstractions.pdf" "https://dlsyscourse.org/slides/7-nn-framework.pdf"
download_file "9 - Normalization Dropout Implementation.pdf" "https://dlsyscourse.org/slides/norm_reg.pdf"
download_file "10 - Convolutional Networks.pdf" "https://dlsyscourse.org/slides/conv_nets.pdf"
download_file "11 - Hardware Acceleration for Linear Algebra.pdf" "https://dlsyscourse.org/slides/11-hardware-acceleration.pdf"
download_file "12 - Hardware Acceleration + GPUs.pdf" "https://dlsyscourse.org/slides/12-gpu-acceleration.pdf"
download_file "15 - Sequence Modeling + RNNs.pdf" "https://dlsyscourse.org/slides/rnns.pdf"
download_file "17 - Transformers and Autoregressive Models.pdf" "https://dlsyscourse.org/slides/transformers.pdf"
download_file "19 - Training Large Models.pdf" "https://dlsyscourse.org/slides/15-training-large-models.pdf"
download_file "20 - Generative Models.pdf" "https://dlsyscourse.org/slides/16-generative-models.pdf"
download_file "22 - Customize Pretrained Models.pdf" "https://dlsyscourse.org/slides/22-augment-pretrained-models.pdf"
download_file "23 - Model Deployment.pdf" "https://dlsyscourse.org/slides/23-model-deployment.pdf"
# --- 下载列表结束 ---
echo "-----------------------------------------"
echo "所有预设的 PDF 均已下载完毕"