Machine Learning/Azure ML (4) ์ธ๋ค์ผํ ๋ฆฌ์คํธํ ๋ฐ์ดํฐ ๋ก๋ read_pandas_dataframe Creates a new Dataflow based on the contents of a given pandas DataFrame. โ Parameters df pandas DataFrame to be parsed and cached at 'temp_folder'. โ temp_folder path to folder that 'df' contents will be written to. โ overwrite_ok If temp_folder exists, whether to allow its contents to be replaced. โ in_memory Whether to read the DataFrame from memory instead of persisting.. Azure ML ์์ 1. Azure ML ์์ ์์ญํ๊ณ ์ฐ๊ฒฐ import azureml.core from azureml.core import Workspace # check core SDK version number print("Azure ML SDK Version: ", azureml.core.VERSION) # load workspace configuration from the config.json file in the current folder. ws = Workspace.from_config() print(ws.name, ws.location, ws.resource_group, ws.location, sep = '\t') 2. ์คํ ๋ง๋ฌ - ๋ถ๋ฌ์จ ์์ ์์ญ ws์ ์คํ ์ด๋ฆ ์ ํ๊ณ ๋ง๋ฌ experiment_name .. AKS ํด๋ฌ์คํฐ ๋ง๋ค๊ธฐ Python : SDK ์ฌ์ฉํ์ฌ AKS ์ฐ๊ฒฐ aks_target = AksCompute(ws,"myaks") deployment_config = AksWebservice.deploy_configuration(cpu_cores = 1, memory_gb = 1) service = Model.deploy(ws, "aksservice", [model], inference_config, deployment_config, aks_target) service.wait_for_deployment(show_output = True) print(service.state) print(service.get_logs()) https://azure.microsoft.com/ko-kr/pricing/ ๊ฐ๊ฒฉ ์ฑ ์ ๊ฐ์ - Azur.. Azure Machine Learning Azure ์ฒดํ ๊ณ์ ๊ฐ์ ํจ : 12๊ฐ์ ์ธ๊ธฐ๋ฌด๋ฃ + 30์ผ ํฌ๋ ๋ง \224,930 12๊ฐ์ ๋ฌด๋ฃ ์ ํ ํญ์ ๋ฌด๋ฃ? ์ ํ Azure Machine Learning ์๋น์ค ์ค๋ช ์ https://docs.microsoft.com/ko-kr/azure/machine-learning/service/ Azure Machine Learning ์๋น์ค ์ค๋ช ์ - ์์ต์, API ์ฐธ์กฐ Azure Machine Learning Service๋ ์ ์ํ๊ฒ ๋ฐ์ดํฐ๋ฅผ ์ค๋นํ๊ณ , ๊ธฐ๊ณ ํ์ต ๋ชจ๋ธ์ ํ์ต ๋ฐ ๋ฐฐํฌํ ์ ์๋ SDK ๋ฐ ์๋น์ค๋ฅผ ์ ๊ณตํฉ๋๋ค. ์๋ ํฌ๊ธฐ ์กฐ์ ์ปดํจํ ๋ฐ ํ์ดํ๋ผ์ธ์ ์ฌ์ฉํ์ฌ ์์ฐ์ฑ์ ๊ฐ์ ํ๊ณ ๋น์ฉ์ ์ค์ด์ธ์. PyTorch, TensorFlow ๋ฐ scikit-learn๊ณผ ๊ฐ์ ์คํ ์์ค Python .. ์ด์ 1 ๋ค์ ํฐ์คํ ๋ฆฌํด๋ฐ Developer๐ค๊ตฌ๋ ํ๊ธฐ
