| | albert-base-v2 | |
| | amazon_comprehend_sagemaker_pipeline | |
| | amazon_demo_product | |
| | athena_ml_workflow_end_to_end | |
| | auto-scaling | |
| | autogluon_tabular_marketplace | |
| | autogluon-sagemaker-pipeline | |
| | autogluon-tabular | |
| | autogluon-tabular-containers | |
| | automate_model_retraining_workflow | |
| | automating_auto_insurance_claim_processing | |
| | AutoML_-_Train_multiple_models_in_parallel | |
| | autopilot-serverless-inference | |
| | bandits_recsys_movielens_testbed | |
| | bandits_statlog_vw_customEnv | |
| | basic-training-container | |
| | bedrock-examples | |
| | bert_attention_head_view | |
| | bert_trition_backend | |
| | byoc-nginx-python | |
| | causal-inference | |
| | churn_prediction_multimodality_of_text_and_tabular | |
| | clarify-explainability-inference-pipelines | |
| | computer-vision-examples | |
| | creative-writing-using-gpt-2-text-generation | |
| | credit_card_fraud_detector | |
| | curating_aws_marketplace_listing_and_sample_notebook | |
| | custom_tensorflow_inference_script_csv_and_tfrecord | |
| | custom-feature-selection | |
| | customer_churn | |
| | customizing_build_train_deploy_project | |
| | data_parallel_bert | |
| | deep_demand_forecasting | |
| | deploy_all_options_xgb | |
| | deploy_huggingface_model_on_Inf1_instance | |
| | deploy_pytorch_model_on_Inf1_instance | |
| | distributed_tensorflow_mask_rcnn | |
| | dw_flow | |
| | end_to_end_music_recommendation | |
| | evaluating_aws_marketplace_models_for_person_counting_use_case | |
| | fairness_and_explainability | |
| | fairness_and_explainability_json | |
| | fairness_and_explainability_json_format | |
| | fairness_and_explainability_jsonlines | |
| | fairness_and_explainability_spark | |
| | fairseq_sagemaker_translate_en2fr | |
| | falcon | |
| | fil_ensemble | |
| | framework-container | |
| | frameworks-tensorflow | |
| | fraud_detection | |
| | fraud_detection_using_graph_neural_networks | |
| | fully_sharded_data_parallel-falcon | |
| | geospatial | |
| | getting_started | |
| | gluon_recommender_system | |
| | gluoncv_yolo_neo | |
| | hf-tgi-bloom7b1 | |
| | huggingface_deploy_instructpix2pix | |
| | huggingface_multiclass_text_classification_20_newsgroups | |
| | huggingface_sentiment_classification | |
| | huggingface_text_classification | |
| | huggingface-inference-recommender | |
| | huggingface-large-model-inference-santacoder | |
| | identify_key_insights_from_textual_document | |
| | Image_Classification_VIT | |
| | implicit_bpr | |
| | improving_industrial_workplace_safety | |
| | inference_pipeline_custom_containers | |
| | inference-benchmarking | |
| | inference-recommender-with-python-sdk | |
| | ingest-with-aws-services | |
| | jit_trace | |
| | JPMML_Models_SageMaker | |
| | keras_bring_your_own | |
| | keras_script_mode_pipe_mode_horovod | |
| | language-modeling | |
| | llm_monitor_byoc | |
| | lmi-aitemplate-stablediff | |
| | local_experiment_tracking | |
| | machine_learning_workflow_abalone | |
| | managed_spot_training_tensorflow_estimator | |
| | ml-lifecycle | |
| | mme-on-gpu | |
| | mnist | |
| | model_monitor_tensorflow | |
| | monitoring_data_quality_of_models | |
| | mpi_on_sagemaker | |
| | multi_modal_parallel_sagemaker_labeling_workflows_with_step_functions | |
| | multi_model_catboost | |
| | multi_model_linear_learner_home_value | |
| | multi_model_pytorch | |
| | multicategory_sec | |
| | multimodal_tabtext | |
| | mxnet_distributed_mnist_neo_inf1 | |
| | mxnet_onnx_ei | |
| | nas_for_llm_with_amt | |
| | nlp_mlops_company_sentiment | |
| | nlp_score_dashboard_sec | |
| | notebook-job-step | |
| | object_detection_with_tensorflow_and_tfrecords | |
| | onnx-roberta-backend | |
| | parameterize-spark-config-pysparkprocessor-pipeline | |
| | pipe_bring_your_own | |
| | prep_data | |
| | preprocessing-audio-data-using-a-machine-learning-model | |
| | product_ratings_with_pipelines | |
| | pyspark_mnist | |
| | python-sdk | |
| | pytorch | |
| | pytorch_cnn_cifar10 | |
| | pytorch_deploy_pretrained_bert_model | |
| | pytorch_extend_container_train_deploy_bertopic | |
| | pytorch_horovod_mnist | |
| | pytorch_multiple_gpu_single_node | |
| | pytorch_smdataparallel_mnist_demo | |
| | pytorch_torchvision | |
| | pytorch_triton_inference_recommender | |
| | pytorch_yolov5_training_and_hpo | |
| | pytorch-ic-model | |
| | pytorch-sagemaker-huggingface | |
| | r_byo_r_algo_hpo | |
| | r_serving_with_fastapi | |
| | r_serving_with_plumber | |
| | rapids_bring_your_own | |
| | resnet_onnx_backend_SME_triton_v2 | |
| | resnet_onnx_pytorch_tensorRT-backend | |
| | resnet_pytorch_python-backend | |
| | resnet50 | |
| | RestRServe_Example | |
| | retail_recommend | |
| | rl_gamerserver_ray | |
| | rl_hvac_coach_energyplus | |
| | rl_mountain_car_coach_gymEnv | |
| | rl_stock_trading_coach_customEnv | |
| | rl_traveling_salesman_vehicle_routing_coach | |
| | rl_unity_ray | |
| | roberta_traced_triton | |
| | roberta-base | |
| | sagemaker_clarify_integration | |
| | sagemaker_job_tracking | |
| | sagemaker_pytorch_model_zoo | |
| | sagemaker-autopilot-pipelines | |
| | sagemaker-debugger | |
| | sagemaker-featurestore | |
| | sagemaker-huggingface-tgi-hosting-examples | |
| | sagemaker-lineage | |
| | sagemaker-pipeline-compare-model-versions | |
| | sagemaker-pipeline-multi-model | |
| | sagemaker-pipeline-parameterization | |
| | sagemaker-script-mode | |
| | scientific_details_of_algorithms | |
| | scikit_learn_bring_your_own_model | |
| | scikit_learn_data_processing_and_model_evaluation | |
| | scikit_learn_iris | |
| | script-mode-container | |
| | script-mode-container-2 | |
| | sentiment_parallel_batch | |
| | seq2seq_translation_en-de | |
| | shadow-console | |
| | single_gpu_single_node | |
| | sklearn | |
| | sklearn-inference-recommender | |
| | sm-train_a_pytorch_model | |
| | smddp_deepspeed_example | |
| | sme_resnet_pytorch_python-backend | |
| | smp-gpt-sharded-data-parallel | |
| | smp-train-gpt-neox-sharded-data-parallel | |
| | smp-train-gptj-sharded-data-parallel-tp | |
| | smp-train-t5-sharded-data-parallel | |
| | stable_diffusion | |
| | streamlit_demo | |
| | studio-scheduling | |
| | t5_pytorch_python-backend | |
| | tensorboard_keras | |
| | tensorflow | |
| | tensorflow_action_on_rule | |
| | tensorflow_moving_from_framework_mode_to_script_mode | |
| | tensorflow_open-images_jpg | |
| | tensorflow_profiling | |
| | tensorflow_script_mode_quickstart | |
| | tensorflow_script_mode_training_and_serving | |
| | tensorflow_serving_using_elastic_inference_with_your_own_model | |
| | tensorflow_single_gpu_single_node | |
| | tensorflow-cloudwatch | |
| | tensorflow2_mnist | |
| | tensorflow2-california-housing-sagemaker-pipelines-deploy-endpoint | |
| | tensort-rt | |
| | Text_Classification_BERT | |
| | text_explainability_sagemaker_algorithm | |
| | text-to-image-fine-tuning | |
| | tf-dali-ensemble-cv | |
| | time_series_deepar | |
| | time_series_forecasting | |
| | timeseries-quantile-selection-dataflow | |
| | training_pipeline_pytorch_mnist | |
| | triton-cv-mme-tensorflow-backend | |
| | using_step_decorator_with_selective_execution | |
| | vision-transformer | |
| | visual_object_detection | |
| | visualization | |
| | workshops | |
| | xgboost_abalone | |
| | xgboost_bring_your_own | |
| | xgboost_ensemble_python-fil-backend | |
| | xgboost_parquet_input_training | |
| | 2_object_detection_train_eval.ipynb | 72.2 KB |
| | algorithms.ipynb | 14.7 KB |
| | Amazon_Jumpstart_AlexaTM_20B.ipynb | 59.5 KB |
| | Amazon_JumpStart_Image_Classification_Benchmarking.ipynb | 50.9 KB |
| | Amazon_JumpStart_Image_Classification.ipynb | 36.1 KB |
| | Amazon_JumpStart_Image_Embedding.ipynb | 17.7 KB |
| | Amazon_JumpStart_Inpainting.ipynb | 34.3 KB |
| | Amazon_JumpStart_Instance_Segmentation.ipynb | 22.0 KB |
| | Amazon_JumpStart_Machine_Translation.ipynb | 17.2 KB |
| | Amazon_JumpStart_Named_Entity_Recognition.ipynb | 29.1 KB |
| | Amazon_JumpStart_NLP_Regression_Free_Training.ipynb | 43.7 KB |
| | Amazon_JumpStart_Object_Detection.ipynb | 36.8 KB |
| | Amazon_JumpStart_Question_Answering.ipynb | 49.9 KB |
| | Amazon_JumpStart_Regression_Free_Training.ipynb | 23.4 KB |
| | Amazon_JumpStart_Semantic_Segmentation_Extract_Image.ipynb | 23.8 KB |
| | Amazon_JumpStart_Semantic_Segmentation.ipynb | 35.5 KB |
| | Amazon_JumpStart_Sentence_Pair_Classification.ipynb | 36.2 KB |
| | Amazon_JumpStart_Text_Classification.ipynb | 18.0 KB |
| | Amazon_JumpStart_Text_Generation.ipynb | 22.7 KB |
| | Amazon_JumpStart_Text_Summarization.ipynb | 17.6 KB |
| | Amazon_JumpStart_Upscaling.ipynb | 31.5 KB |
| | Amazon_JumpStart_Zero_Shot_Text_Classification.ipynb | 42.1 KB |
| | Amazon_Tabular_Classification_AutoGluon.ipynb | 29.1 KB |
| | Amazon_Tabular_Regression_LightGBM_CatBoost.ipynb | 31.0 KB |
| | Amazon_Tabular_Regression_TabTransformer.ipynb | 30.3 KB |
| | Amazon_TensorFlow_Image_Classification.ipynb | 41.0 KB |
| | Amazon_Tensorflow_Object_Detection.ipynb | 42.7 KB |
| | ap-batch-transform.ipynb | 33.7 KB |
| | automatic-speech-recognition.ipynb | 28.8 KB |
| | autopilot_customer_churn_high_level_with_evaluation.ipynb | 43.4 KB |
| | autopilot_ts_data_merge.ipynb | 39.9 KB |
| | Batch Transform - breast cancer prediction with high level SDK.ipynb | 36.7 KB |
| | Batch Transform - breast cancer prediction with lowel level SDK.ipynb | 54.8 KB |
| | bias_detection_with_predicted_label_and_facet_datasets.ipynb | 46.8 KB |
| | bloom-z-176b-few-shot-and-zero-shot-learning.ipynb | 153.8 KB |
| | boto3_scikit_retrain_model_and_deploy_to_existing_endpoint.ipynb | 40.6 KB |
| | bring_your_own_container.ipynb | 6.6 KB |
| | build_gan_with_pytorch.ipynb | 53.7 KB |
| | churn-prediction-lightgbm-catboost-tabtransformer-autogluon.ipynb | 70.2 KB |
| | custom_dog_image_generator.ipynb | 37.6 KB |
| | data_analysis_of_ground_truth_image_classification_output.ipynb | 34.5 KB |
| | deepar_chicago_traffic_violations.ipynb | 39.1 KB |
| | DeployStableCascade.ipynb | 19.2 KB |
| | distilgpt2-tgi.ipynb | 25.0 KB |
| | djl_deepspeed_deploy_opt30b_no_custom_inference_code.ipynb | 37.7 KB |
| | djl_deepspeed_deploy_opt30b.ipynb | 44.5 KB |
| | download_weights.ipynb | 27.8 KB |
| | Dynamic Pricing with Causal Machine Learning and Optimization on Amazon SageMaker.ipynb | 53.8 KB |
| | endpoints.ipynb | 6.1 KB |
| | EnsembleLearnerCensusIncome.ipynb | 48.7 KB |
| | explainability_with_pdp.ipynb | 45.1 KB |
| | fairness_and_explainability_jsonlines_format.ipynb | 92.4 KB |
| | fairness_and_explainability_outputs.ipynb | 125.0 KB |
| | falcon-7b-instruction-domain-adaptation-finetuning.ipynb | 34.2 KB |
| | feature_store_securely_store_images.ipynb | 39.9 KB |
| | financial_payment_classification.ipynb | 34.4 KB |
| | forecast_example.ipynb | 32.8 KB |
| | frameworks.ipynb | 10.6 KB |
| | from_unlabeled_data_to_deployed_machine_learning_model_ground_truth_demo_image_classification.ipynb | 93.8 KB |
| | get_started_mnist_train_outputs.ipynb | 62.6 KB |
| | GPT-J-6B_DJLServing_with_PySDK.ipynb | 22.5 KB |
| | GPT-J-6B-model-parallel-inference-DJL.ipynb | 18.3 KB |
| | gpt2-large-tgi.ipynb | 25.1 KB |
| | gpt2-tgi.ipynb | 22.7 KB |
| | gpt2-xl-tgi.ipynb | 26.6 KB |
| | granite-code-instruct.ipynb | 40.2 KB |
| | GT_semantic_segmentation_to_COCO.ipynb | 17.7 KB |
| | hello_world_workflow.ipynb | 43.2 KB |
| | hf-tgi-flan-t5-xl.ipynb | 58.6 KB |
| | HPO_Analyze_TuningJob_Results.ipynb | 27.1 KB |
| | image-classification-with-shutterstock-datasets.ipynb | 28.7 KB |
| | image-generation-stable-diffusion.ipynb | 31.4 KB |
| | ingest_image_data.ipynb | 13.2 KB |
| | ingest_tabular_data.ipynb | 14.8 KB |
| | ingest_text_data.ipynb | 23.3 KB |
| | instant-recommendations.ipynb | 10.6 KB |
| | instruction-fine-tuning-flan-t5.ipynb | 38.7 KB |
| | JumpStart_Stable_Diffusion_Inference_Only.ipynb | 43.2 KB |
| | kmeans_bring_your_own_model.ipynb | 17.6 KB |
| | kmeans_mnist.ipynb | 17.5 KB |
| | linear_learner_mnist.ipynb | 23.5 KB |
| | Linear_Learner_Regression_csv_format.ipynb | 34.7 KB |
| | open-assistant-chatbot.ipynb | 21.2 KB |
| | pyspark_mnist_custom_estimator.ipynb | 18.8 KB |
| | pyspark_mnist_pca_mllib_kmeans.ipynb | 20.1 KB |
| | pytorch_mnist_elastic_inference.ipynb | 25.4 KB |
| | question_answering_jumpstart_knn.ipynb | 46.3 KB |
| | question_answering_pinecone_llama-2_jumpstart.ipynb | 53.9 KB |
| | question_answering_text_embedding_llama-2_jumpstart.ipynb | 37.2 KB |
| | R_binary_classification_algorithms_comparison.ipynb | 50.2 KB |
| | r_sagemaker_hello_world.ipynb | 13.8 KB |
| | r_xgboost_batch_transform.ipynb | 26.7 KB |
| | r_xgboost_hpo_batch_transform.ipynb | 42.9 KB |
| | risk_bucketing.ipynb | 20.2 KB |
| | sagemaker_autopilot_abalone_parquet_input.ipynb | 11.5 KB |
| | sagemaker_autopilot_direct_marketing.ipynb | 27.0 KB |
| | sagemaker_autopilot_neo4j_portfolio_churn.ipynb | 33.6 KB |
| | SageMaker_Keyspaces_ml_example.ipynb | 30.0 KB |
| | sagemaker-lightgbm-distributed-training-dask.ipynb | 40.6 KB |
| | sagemaker-lineage-multihop-queries_outputs.ipynb | 337.5 KB |
| | SageMaker-Monitoring-Bias-Drift-for-Batch-Transform-JSON-Lines.ipynb | 80.6 KB |
| | SageMaker-Monitoring-Bias-Drift-for-Batch-Transform.ipynb | 61.3 KB |
| | sagemaker-neo-tf-unet.ipynb | 22.6 KB |
| | scikit_learn_model_registry_batch_transform.ipynb | 31.2 KB |
| | SEC_Retrieval_Summarizer_Scoring.ipynb | 77.4 KB |
| | serverless-model-registry.ipynb | 20.7 KB |
| | sklearn_multi_model_endpoint_home_value.ipynb | 62.3 KB |
| | Sklearn_on_SageMaker_end2end.ipynb | 24.4 KB |
| | smp-finetuning-gpt-neox-fsdp-tp.ipynb | 43.9 KB |
| | smp-train-gpt-neox-fsdp-tp.ipynb | 45.6 KB |
| | sparkml_serving_emr_mleap_abalone.ipynb | 45.8 KB |
| | step_functions_mlworkflow_scikit_learn_data_processing_and_model_evaluation.ipynb | 57.3 KB |
| | tensorflow_BYOM_iris.ipynb | 18.3 KB |
| | text-embedding-sentence-similarity.ipynb | 38.2 KB |
| | text-generation-chatbot.ipynb | 37.0 KB |
| | text-generation-falcon.ipynb | 25.5 KB |
| | text-generation-few-shot-learning.ipynb | 62.7 KB |
| | text-generation-open-llama.ipynb | 12.4 KB |
| | text2text-generation-Batch-Transform.ipynb | 31.1 KB |
| | text2text-generation-bloomz.ipynb | 60.7 KB |
| | text2text-generation-flan-t5-ul2.ipynb | 45.8 KB |
| | text2text-generation-flan-t5.ipynb | 45.7 KB |
| | tf-resnet-profiling-multi-gpu-multi-node.ipynb | 16.5 KB |
| | tgi-bloom-560m.ipynb | 23.2 KB |
| | tgi-gpt-neox-20b.ipynb | 23.2 KB |
| | Transcription_on_SM_endpoint.ipynb | 37.2 KB |
| | upgrade_to_v2.ipynb | 9.8 KB |
| | using-dataset-product-from-aws-data-exchange-with-ml-model-from-aws-marketplace.ipynb | 24.9 KB |
| | vilt-b32-finetuned-vqa.ipynb | 26.4 KB |
| | xgboost_customer_churn_outputs.ipynb | 1.5 MB |
| | xgboost_mnist.ipynb | 40.8 KB |
| | xgboost_multi_model_endpoint_home_value.ipynb | 58.9 KB |
| | xgboost-census-debugger-rules.ipynb | 57.3 KB |
| | xgboost-inference-recommender.ipynb | 30.0 KB |