- PyTorch 1.x Reinforcement Learning Cookbook
- Yuxi (Hayden) Liu
- 191字
- 2021-06-24 12:34:37
There's more...
Some of you may question the necessity of installing Anaconda and using conda to manage packages since it is easy to install packages with pip. In fact, conda is a better packaging tool than pip. We mainly use conda for the following four reasons:
- It handles library dependencies nicely: Installing a package with conda will automatically download all of its dependencies. However, doing so with pip will lead to a warning, and installation will be aborted.
- It solves conflicts of packages gracefully: If installing a package requires another package of a specific version (let's say 2.3 or after, for example), conda will update the version of the other package automatically.
- It creates a virtual environment easily: A virtual environment is a self-contained package directory tree. Different applications or projects can use different virtual environments. All virtual environments are isolated from each other. It is recommended to use virtual environments so that whatever we do for one application doesn't affect our system environment or any other environment.
- It is also compatible with pip: We can still use pip in conda with the following command:
conda install pip
推薦閱讀
- Word 2003、Excel 2003、PowerPoint 2003上機指導與練習
- 工業機器人技術及應用
- Multimedia Programming with Pure Data
- Storm應用實踐:實時事務處理之策略
- 工業機器人安裝與調試
- Machine Learning with the Elastic Stack
- 零起點學西門子S7-200 PLC
- 軟件構件技術
- Bayesian Analysis with Python
- Unreal Development Kit Game Design Cookbook
- 穿越計算機的迷霧
- 從零開始學ASP.NET
- Keras Reinforcement Learning Projects
- 實戰突擊
- Microsoft 365 Mobility and Security:Exam Guide MS-101