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文章介绍了如何使用conda管理Python虚拟环境，并连接到JupyterNotebook进行时序分类和回归预测的学习。 在下载tsai项目后，通过激活特定环境并安装所需库，然后使用`python-mipykernelinstall--name`命令将环境与Jupyter连接，解决运行ipynb文件时模块缺失的问题。 tsai是一个先进的时间序列和序列深度学习库。 是建立在Pytorch &fastai之上的开源深度学习包，可以用于完成关于时间序列的多种任务，如分类、回归、预测、插补等任务。 tsai是一个基于PyTorch和fastai构建的开源深度学习库,专注于时间序列和序列数据的最先进技术,可用于分类、回归、预测等多种任务。
She was the first woman to hold the presidency in taiwan's history Modified the multimodal head to properly handle sequence predictions. Tsai was born in taipei and earned bachelor's and master's degrees in law from national taiwan university and cornell university, respectively
She went to england to study law at the london school of economics, where she received a phd in 1984, and became a law professor.
tsai - 基于 fastai 和 Pytorch 的时间序列/序列数据库的实用深度学习 A number of tutorials have been created to help you get started to use tsai with time series data Please, feel free to open the notebooks (you can open them in colab if you want) and tweak them to do your own experiments. New features applied necessary changes to the tsai library for full support on mps devices
Bugs squashed updated tsit and tssequencer models to resolve compatibility issues on the mps backend
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