From 4d4118ddb389cc73f53d607c0cbb6e9ebadb3083 Mon Sep 17 00:00:00 2001 From: RichardScottOZ Date: Sat, 13 Apr 2024 17:28:39 +0930 Subject: [PATCH] Minor edits --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 8afa3be..1ca8515 100644 --- a/README.md +++ b/README.md @@ -15,13 +15,13 @@ To enable you to easily access the core implementation of the system, we did sev ## System Overview Our mini deep learning system consists of four services and one storage system, they are: -- **[Dataset management service](https://github.com/orca3/MiniAutoML/tree/main/data-management)**, designed for storing and fetching dataset. +- **[Dataset management service](https://github.com/orca3/MiniAutoML/tree/main/data-management)**, designed for storing and fetching datasets. - **[Model training service](https://github.com/orca3/MiniAutoML/tree/main/training-service)**, designed for running model training code. - **[Metadata store service](https://github.com/orca3/MiniAutoML/tree/main/metadata-store)**, designed for storing model metadata, such as model name, model version and model algorithm. - **[Prediction service](https://github.com/orca3/MiniAutoML/tree/main/prediction-service)**, designed to execute models to process customer’s prediction requests. - **MinIO storage**, an object storage similar to AWS S3 but can run on your local computer. -In the book [Engineering Deep Learning Systems](http://mng.bz/GGgN), each of these serivces gets their own chapter. To play with the system locally, please install the [system requirements](https://github.com/orca3/MiniAutoML#system-requirement) and then follow the instructions in the [lab](https://github.com/orca3/MiniAutoML#lab) section. +In the book [Engineering Deep Learning Systems](http://mng.bz/GGgN), each of these services gets their own chapter. To play with the system locally, please install the [system requirements](https://github.com/orca3/MiniAutoML#system-requirement) and then follow the instructions in the [lab](https://github.com/orca3/MiniAutoML#lab) section. ## System Requirements The installation of system requirements are not included in the `scripts` folder. Please make sure those requirements are met before executing scripts in the `scripts` folder. @@ -64,7 +64,7 @@ In the root folder you'll find a Maven project description file `pom.xml`, which ## Lab -After installing the [system requirements](https://github.com/orca3/MiniAutoML#system-requirement): docker, Minio, grpcurl and JQ, you can use our lab scripts to setup the sample deep learning system locally and start to play with it, such building a NLP model. By exeucting these scripts one by one, you will see a complete deep learning cycle, from data collection to model training and model serving. +After installing the [system requirements](https://github.com/orca3/MiniAutoML#system-requirement): docker, Minio, grpcurl and JQ, you can use our lab scripts to setup the sample deep learning system locally and start to play with it, such building a NLP model. By executing these scripts one by one, you will see a complete deep learning cycle, from data collection to model training and model serving. It is strongly recommended to create and activate a brand new Conda environment before running any lab scripts to avoid long setup times and possible failures. You can do so by running ```shell