retrieve ( 'mxnet', region, version = '1.7.0', py_version = 'p圓', instance_type = 'ml.m5.2xlarge', image_scope = 'inference', ) ecr_uri_prefix = account + '.' + '.'. retrieve ( 'mxnet', region, version = '1.7.0', py_version = 'p圓', instance_type = 'ml.m5.2xlarge', image_scope = 'training', ) registry_uri_inference = sagemaker. get_caller_identity () registry_uri_training = sagemaker. sts_regional_endpoint ( region ) ) account = client. client ( 'sts', region_name = region, endpoint_url = utils. boto_region_name role = get_execution_role () client = session. default_bucket () prefix = 'sagemaker/autogluon-tabular' region = session. set_option ( 'display.max_rows', 10 ) # Account/s3 setup session = sagemaker. set_option ( 'display.max_columns', 500 ) pd. Import os import sys import boto3 import sagemaker from time import sleep from collections import Counter import numpy as np import pandas as pd from sagemaker import get_execution_role, local, Model, utils, s3 from sagemaker.estimator import Estimator from sagemaker.predictor import Predictor from rializers import CSVSerializer from serializers import StringDeserializer from trics import accuracy_score, classification_report from import display, HTML from import InteractiveShell # Print settings InteractiveShell. Get started with SageMaker Feature Store.Amazon Keyspaces (for Apache Cassandra).SageMaker Algorithms with Pre-Trained Model Examples by Problem Type.Pipelines with NLP for Product Rating Prediction.Music Streaming Service: Customer Churn Detection.Understanding Trends in Company Valuation with NLP.

Iris Training and Prediction with Sagemaker Scikit-learn.Regression with Amazon SageMaker XGBoost algorithm.Orchestrate Jobs to Train and Evaluate Models with Amazon SageMaker Pipelines.Fairness and Explainability with SageMaker Clarify.

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Use SageMaker Batch Transform for PyTorch Batch Inference.

Deploying pre-trained PyTorch vision models with Amazon SageMaker Neo.

Run a SageMaker Experiment with MNIST Handwritten Digits Classification.

Train a SKLearn Model using Script Mode.

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Sagemaker clarify