From 14005e35520331547d76f6fb11344ea19a353af1 Mon Sep 17 00:00:00 2001 From: sanyhe Date: Sun, 5 Jan 2025 12:07:32 +0800 Subject: [PATCH] docs: update commands info. --- README.md | 4 ++-- docs/source/Home/Introduction.md | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index b934b3d..f21c6d7 100644 --- a/README.md +++ b/README.md @@ -190,7 +190,7 @@ On Jupyter Notebook / Google Colab: + There are five built-in data sets corresponding to five kinds of model pattern. -+ The generated output directory `geopi_output` and `geopi_tracking` will be on desktop by default. ++ The generated output directory `geopi_output` and `geopi_tracking` will be on the directory where you run this command. ### Case 2: Run with your own data set on desktop for model training and model inference @@ -253,7 +253,7 @@ On Jupyter Notebook / Google Colab: + The training data in our pipeline will be divided into the train set and test set used for training the ML model and evaluating the model's performance. The score includes two types. The first type is the scores from the prediction on the test set while the second type is cv scores from the cross validation on the train set. -+ The generated output directory 'geopi_output' and 'geopi_tracking' will be on the directory where you run this command. ++ The generated output directory `geopi_output` and `geopi_tracking` will be on the directory where you run this command. ### Case 5: Activate MLflow web interface diff --git a/docs/source/Home/Introduction.md b/docs/source/Home/Introduction.md index 94c6a97..cf7ef7d 100644 --- a/docs/source/Home/Introduction.md +++ b/docs/source/Home/Introduction.md @@ -192,7 +192,7 @@ On Jupyter Notebook / Google Colab: + There are five built-in data sets corresponding to five kinds of model pattern. -+ The generated output directory `geopi_output` and `geopi_tracking` will be on desktop by default. ++ The generated output directory `geopi_output` and `geopi_tracking` will be on the directory where you run this command. ### Case 2: Run with your own data set on desktop for model training and model inference @@ -255,7 +255,7 @@ On Jupyter Notebook / Google Colab: + The training data in our pipeline will be divided into the train set and test set used for training the ML model and evaluating the model's performance. The score includes two types. The first type is the scores from the prediction on the test set while the second type is cv scores from the cross validation on the train set. -+ The generated output directory 'geopi_output' and 'geopi_tracking' will be on the directory where you run this command. ++ The generated output directory `geopi_output` and `geopi_tracking` will be on the directory where you run this command. ### Case 5: Activate MLflow web interface