Urban sound classification using Deep Learning
aqibsaeed/Urban-Sound-Classification 排名第 17,852，有 520 个星标。
aqibsaeed/Urban-Sound-Classification 排名第 17,852，此处有 8 个同类条目；awjuliani/TF-Tutorials 排名第 17,853。
| 名称 | 排名 | 指标 |
|---|---|---|
| mgechev/guess-next | 17,818 |
|
| Callous-0923/agent-study | 17,826 |
|
| dpkingma/nips14-ssl | 17,835 |
|
| Jack47/hack-SysML | 17,845 |
|
| awjuliani/TF-Tutorials | 17,853 |
|
| akshaybahadur21/Autopilot | 17,869 |
|
| srush/annotated-s4 | 17,879 |
|
| HayatoHongo/EveryonesLLM | 17,889 |
|
| 参数 | 值 |
|---|---|
| 语言 | Jupyter Notebook |
| 类别 | Tutorials |
| 子类别 | ML/AI fundamentals |
| 星标数 | 520 |
| 分叉数 | 239 |
| 贡献者 | 4 |
| 创建日期 | 2016-09-03 |
| 更新日期 | 2026-09-02 |
| 1 天星标数 | 0 |
| 7 天星标数 | 0 |
| 排名 | 17,852 |
| 上次排名 | 17,636 |
| 排名变化 | -216 |
| 7 天星标排名 | 16,331 |
| 上次 7 天星标排名 | 16,339 |
| 7 天星标排名变化 | 8 |
| 总星标排名 | 18,780 |
| 上次总星标排名 | 18,757 |
| 总星标排名变化 | -23 |
| 国家 | Netherlands |
Urban Sound Classification Notebooks Feedforward Network (Blogpost) Convolutional Network (Blogpost) Recurrent Network Tools Python 3. 5 (or above) is used during development and following libraries are required to run the code provided in the notebook: Tensorflow 2. x Numpy Matplotlib Librosa Dataset The UrbanSound8k dataset used for model training, can be downloaded from the following link. Another related dataset that can be used is Google's AudioSet.
aqibsaeed/Urban-Sound-Classification 有 520 个星标和 239 个分叉。
aqibsaeed/Urban-Sound-Classification 排名第 17,852。
aqibsaeed/Urban-Sound-Classification 有 520 个星标，语言为 Jupyter Notebook，类别为 Tutorials。
aqibsaeed/Urban-Sound-Classification 与 awjuliani/TF-Tutorials 比较，后者排名第 17,853，有 520 个星标。
Convolutional Network (Blogpost)
Python 3.5 (or above) is used during development and following libraries are required to run the code provided in the notebook:
The UrbanSound8k dataset used for model training, can be downloaded from the following link.
Another related dataset that can be used is Google's AudioSet.