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Hands-On Machine Learning with ML.NET, published by Packt Download a free PDF If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost. Simply click on the link to claim your free PDF. ...
完整的代码在 GitHub 上获取,地址是:https://github.com/ageron/handson-ml。代码形式是 Jupyter Notebook。 3.1 创建工作环境 首先你需要安装Python,获取地址:https://www.python.org/。 接下来需要创建一个工作空间目录,在终端输入以下命令(在提示符 $ 之后): $exportML_PATH="$HOME/ml"# You can change ...
Next, clone this project by opening a terminal and typing the following commands (do not type the first$signs on each line, they just indicate that these are terminal commands): $ git clone https://github.com/ageron/handson-ml2.git $ cd handson-ml2 Next, run the following commands: $...
《Hands-On Machine Learning with Scikit-Learn and TensorFlow Concepts, Tools, and Techniques to Build Intelligent Systems》书名实在太长,后面就就直接叫《Hands on Sklearn and TF》吧。 无意中发现这本书在GitHub上已经有了中译本,感谢ApacheCN的各位大佬,链接如下:https://github.com/apachecn/hands_on_...
3.Hands-on Machine Learning with Scikit-Learn and TensorFlow https://github.com/apachecn/hands_on_Ml_with_Sklearn_and_TF https://www.jianshu.com/p/49bfb59b96b7 https://github.com/ageron/handson-ml ubuntu安装 从清华大学开源软件网站上选择合适的源文件并下载 ...
https://github.com/ageron/handson-ml/tree/master/datasets/housing Create the Workspace: 操作系统最好用Ubuntu16.04 创建工作区: $ export ML_PATH="$HOME/ml" # You can change the path if you prefer $ mkdir -p $ML_PATH 接下来是创建你自己的Python环境,本书中作者推荐Python3 虽然Python2.7+也...
OReilly.Hands-On.Machine.Learning.with.Scikit-Learn.and.TensorFlow.翻译以及读书心得--p41-53,程序员大本营,技术文章内容聚合第一站。
supervised versus unsupervised learning, online versus batch learning, instance-based versus model-based learning. Then we will look at the workflow of a typical ML project, discuss the main challenges you may face, and cover how to evaluate and fine-tune a Machine Learning system. This chapter...
Hands on Machine Learning with sklearn and TensorFlow —— 一个完整的机器学习项目(加州房地产) 数据集地址:https://github.com/ageron/handson-ml/tree/master/datasets 先行知识准备:NumPy,Pandas,Matplotlib的模块使用 机器学习项目流程(一般):可视化数据,发现规律...