MobileNet
Lightweight networks and MobileNet
复杂的网络需要大量的计算资源，如GPU。然而，事实证明在大多数情况下，一个参数数量少得多的模型仍然可以被训练得表现相当好。换句话说，模型复杂性的增加通常会导致模型性能的小幅（非比例）提高。我们在模块的开始阶段训练MNIST数字分类时观察到了这一点。
Computer vision with PyTorch (Dense && Convolutional layers)
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Task
use image classification tasks to learn about convolutional neural networks, and then see how pre-trained networks and transfer learning can improve our models and solve real-world problems.
Building the model layers
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Datasets & DataLoaders & Transforms
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Load data with PyTorch Datasets and DataLoaders
PyTorch provides two data primitives: torch.utils.data.DataLoader and torch.utils.data.Dataset that allow you to use pre-loaded datasets as well as your own data. Dataset stores the samples and their corresponding labels, and DataLoader wraps an iterable around the Dataset to enable easy access to the samples.
PyTorch-Introduction
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Introduction
- An open source machine learning framework
- A Python package that provides two high-level features:
- Tensor computation with strong GPU acceleration
- Deep neural networks built on a tape-based autograd system
机器学习 by 李宏毅(1)
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Hello World
发表于
更新于
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Welcome to Hexo! This is your very first post. Check documentation for more info. If you get any problems when using Hexo, you can find the answer in troubleshooting or you can ask me on GitHub.
Maven 项目管理
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Android应用基础知识
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