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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
AI实战-practicalAI 中文版
| Date | Stars |
|---|---|
| 2026-07-24 | 6905 |
| 2026-07-25 | 6903 |
| 2026-07-28 | 6903 |
| 2026-07-30 | 6903 |
| 2026-08-06 | 6903 |
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# AI实战-[practicalAI](https://github.com/LisonEvf/practicalAI-cn) 中文版 [](https://colab.research.google.com/) [](https://github.com/LisonEvf/practicalAI-cn/blob/master/LICENSE) [](https://github.com/GokuMohandas) [](https://github.com/MLEveryday/practicalAI-cn) 让你有能力使用机器学习从数据中获取有价值的见解。 - 🔥 使用 [PyTorch](https://pytorch.org/) 实现基本的机器学习算法和深度神经网络。 - 🖥️ 不需要任何设置，在浏览器中使用 [Google Colab](https://colab.research.google.com/) 运行所有程序。 - 📦 不仅仅是教程，而是学习产品级的面向对象机器学习编程。 ## Notebooks |基础|深度学习|进阶|主题| |-|-|-|-| |📓 [Notebooks](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/00_Notebooks.ipynb)|🔥 [PyTorch](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/07_PyTorch.ipynb)|📚 [高级循环神经网络 Advanced RNNs](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/14_Advanced_RNNs.ipynb)|📸 [计算机视觉 Computer Vision](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/15_Computer_Vision.ipynb)| |🐍 [Python](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/01_Python.ipynb)|🎛️ [多层感知 Multilayer Perceptrons](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/08_Multilayer_Perceptron.ipynb)|🏎️ Highway and Residual Networks|⏰ 时间序列分析 Time Series Analysis| |🔢 [NumPy](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/02_NumPy.ipynb)|🔎 [数据和模型 Data & Models](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/09_Data_and_Models.ipynb)|🔮 自编码器 Autoencoders|🏘️ Topic Modeling| | 🐼 [Pandas](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/03_Pandas.ipynb) |📦 [面向对象的机器学习 Object-Oriented ML](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/10_Object_Oriented_ML.ipynb)|🎭 生成对抗网络 Generative Adversarial Networks|🛒 推荐系统 Recommendation Systems| |📈 [线性回归 Linear Regression](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/04_Linear_Regression.ipynb)|🖼️ [卷积神经网络 Convolutional Neural Networks](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/11_Convolutional_Neural_Networks.ipynb)|🐝 空间变换模型 Spatial Transformer Networks|🗣️ 预训练语言模型 Pretrained Language Modeling| |📊 [逻辑回归 Logistic Regression](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/05_Logistic_Regression.ipynb)|📝 [嵌入层 Embeddings](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/12_Embeddings.ipynb)||🤷 多任务学习 Multitask Learning| |🌳 [随机森林 Random Forests](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/06_Random_Forests.ipynb)|📗 [递归神经网络 Recurrent Neural Networks](https://nbviewer.jupyter.org/github/LisonEvf/practicalAI-cn/blob/master/notebooks/13_Recurrent_Neural_Networks.ipynb)||🎯 Low Shot Learning| |💥 k-均值聚类 KMeans Clustering|||🍒 强化学习 Reinforcement Learning| ## 查看 notebooks 如果不需要运行 notebooks，使用 Jupyter nbviewer 就可以方便地查看它们。 将 `https://github.com/` 替换为 `https://nbviewer.jupyter.org/github/` ，或者打开 `https://nbviewer.jupyter.org` 并输入 notebook 的 URL。 ## 运行 notebooks 1. 在本项目的 [`notebooks`](/notebooks/) 文件夹获取 notebook； 2. 你可以在 Google Colab（推荐）或本地电脑运行这些 notebook； 3. 点击一个 notebook，然后替换URL地址中 `https://github.com/` 为 `https://colab.research.google.com/github/` ，或者使用这个 [Chrome扩展](https://chrome.google.com/webstore/detail/open-in-colab/iogfkhleblhcpcekbiedikdehleodpjo) 一键完成； 4. 登录你自己的 Google 账户； 5. 点击工具栏上的 `复制到云端硬盘`，会在一个新的标签页打开 notebook； <img src="images/copy_to_drive.png"> 5. 通过去掉标题中的`副本`完成 notebook 重命名； 6. 运行代码、修改等，所有这些都会自动保存到你的个人 Google Drive。 ## 贡献 notebooks 1. 修改后下载 Google Colab notebook 为 .ipyn
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:6e19841fba204ede, topic:deep-learning, topic:pytorch