AWS Machine Learning

AUGUST 10, 2023

As recommended by AWS as a best practice , customers have used separate accounts to simplify policy management for users and isolate resources by workloads and account. SageMaker services, such as Processing, Training, and Hosting, collect metrics and logs from the running instances and push them to users’ Amazon CloudWatch accounts.

Scripts 75

Scripts Accountability Metrics APIs 75

AWS Machine Learning

SEPTEMBER 12, 2023

Solution overview Scalable Capital’s ML infrastructure consists of two AWS accounts: one as an environment for the development stage and the other one for the production stage. The function then relays the classification back to CRM through the API Gateway public endpoint.

Management 90

Management APIs CRM Metrics 90

AWS Machine Learning

FEBRUARY 19, 2024

Inference API – The server exposes an API that allows client applications to send input data and receive predictions from the deployed models. Different request handlers will provide support for the Inference API , Management API , or other APIs available from various plugins.

APIs 88

APIs Engineering Scripts Metrics 88

AWS Machine Learning

MAY 8, 2023

In this post, we address these limitations by implementing the access control outside of the MLflow server and offloading authentication and authorization tasks to Amazon API Gateway , where we implement fine-grained access control mechanisms at the resource level using Identity and Access Management (IAM).

APIs 68

APIs Government Accountability Scripts 68

AWS Machine Learning

JANUARY 5, 2024

Continuous integration and continuous delivery (CI/CD) pipeline – Using the customer’s GitHub repository enabled code versioning and automated scripts to launch pipeline deployment whenever new versions of the code are committed. Wipro has used the input filter and join functionality of SageMaker batch transformation API.

Management 103

Management APIs Engineering Government 103

AWS Machine Learning

AUGUST 29, 2023

This architecture design represents a multi-account strategy where ML models are built, trained, and registered in a central model registry within a data science development account (which has more controls than a typical application development account).

Scripts 70

Scripts APIs Enterprise Accountability 70

AWS Machine Learning

NOVEMBER 24, 2023

SageMaker Canvas now collects Amazon CloudWatch metrics that provide insight into app usage and idleness. All that is needed to do is change the line of code calling the DeleteApp API into CreateApp , as well as updating the cron expression to reflect the desired app creation time.

APIs 86

APIs Metrics Engineering Scripts 86

AWS Machine Learning

SEPTEMBER 8, 2023

Amazon Rekognition makes it easy to add image analysis capability to your applications without any machine learning (ML) expertise and comes with various APIs to fulfil use cases such as object detection, content moderation, face detection and analysis, and text and celebrity recognition, which we use in this example.

APIs 90

APIs Scripts Entertainment Personalization 90

AWS Machine Learning

JULY 24, 2023

If the model changes on the server side, the client has to know and change its API call to the new endpoint accordingly. Based on these metrics an informed decision can be made. Clone the Github repository The GitHub repo provides all the scripts necessary to deploy models using FastAPI on NeuronCores on AWS Inferentia instances.

Scripts 70

Scripts APIs Engineering Best practices 70

AWS Machine Learning

FEBRUARY 6, 2023

Together with the implementation details in a corresponding example Jupyter notebook , you will have tools available to perform model selection by exploring pareto frontiers, where improving one performance metric, such as accuracy, is not possible without worsening another metric, such as throughput.

APIs 69

APIs Scripts Metrics Benchmark 69

Totango

APRIL 26, 2021

Download Campaign Metrics for Targeted Users. Campaigns, SuccessPlays, Account, and User segments with more than one collection criteria now returns accurate results when all the collection criteria match the same collection record. You can also enable a walkthrough script with a script UR L. .

Scripts 62

Scripts APIs Customer retention Enterprise 62

AWS Machine Learning

MAY 10, 2023

It provides a suite of tools for visualizing training metrics, examining model architectures, exploring embeddings, and more. When they create a SageMaker training job, domain users can use TensorBoard using the SageMaker Python SDK or Boto3 API. is your training script, and simple_tensorboard.ipynb launches the SageMaker training job.

Scripts 71

Scripts Metrics Construction APIs 71

AWS Machine Learning

APRIL 29, 2024

This often means the method of using a third-party LLM API won’t do for security, control, and scale reasons. It provides an approachable, robust Python API for the full infrastructure stack of ML/AI, from data and compute to workflows and observability. The following figure illustrates this workflow.

APIs 93

APIs Engineering Scripts Management 93

AWS Machine Learning

AUGUST 30, 2023

For a quantitative analysis of the generated impression, we use ROUGE (Recall-Oriented Understudy for Gisting Evaluation), the most commonly used metric for evaluating summarization. This metric compares an automatically produced summary against a reference or a set of references (human-produced) summary or translation.

Healthcare 105

Healthcare APIs Scripts Metrics 105

AWS Machine Learning

MARCH 1, 2023

Flywheel creates a data lake (in Amazon S3) in your account where all the training and test data for all versions of the model are managed and stored. Based on the quality metrics for the existing and new model versions, you set the active model version to be the version of the flywheel model that you want to use for inference jobs.

APIs 66

APIs Metrics Accountability Scripts 66

AWS Machine Learning

JANUARY 19, 2024

The goal of NAS is to find the optimal architecture for a given problem by searching over a large set of candidate architectures using techniques such as gradient-free optimization or by optimizing the desired metrics. The performance of the architecture is typically measured using metrics such as validation loss. Choose Request.

Metrics 91

Metrics Scripts Benchmark Enterprise 91

AWS Machine Learning

DECEMBER 21, 2022

The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account. A new optional parameter TableFormat can be set either interactively using Amazon SageMaker Studio or through code using the API or the SDK. put_record API to ingest individual records or to handle streaming sources.

Scripts 71

Scripts Engineering APIs Big data 71

AWS Machine Learning

NOVEMBER 1, 2022

Autopilot training jobs start their own dedicated SageMaker backend processes, and dedicated SageMaker API calls are required to start new training jobs, monitor training job statuses, and invoke trained Autopilot models. For this walkthrough, complete the following prerequisite steps: Set up an AWS account. SageMaker pipeline steps.

Scripts 74

Scripts APIs Metrics Engineering 74

AWS Machine Learning

JUNE 27, 2023

By enabling effective management of the ML lifecycle, MLOps can help account for various alterations in data, models, and concepts that the development of real-time image recognition applications is associated with. This step produces an expanded report containing the model’s metrics.

Engineering 90

Engineering APIs Scripts Entertainment 90

AWS Machine Learning

MAY 31, 2023

Triton with PyTorch backend The PyTorch backend is designed to run TorchScript models using the PyTorch C++ API. Alternatively, you can use ensemble models or business logic scripting. Prerequisites You first need an AWS account and an AWS Identity and Access Management (IAM) administrator user. We save the model as a model.pt

APIs 78

APIs Scripts Engineering Accountability 78

AWS Machine Learning

SEPTEMBER 2, 2022

To replicate the results reported in this post, the only prerequisite is an AWS account. In this account, we create an EKS cluster and an Amazon FSx for Lustre file system. We also push container images to an Amazon Elastic Container Registry (Amazon ECR) repository in the account. script in the fsx folder.

Scripts 76

Scripts Metrics Accountability APIs 76

AWS Machine Learning

NOVEMBER 21, 2022

Evaluate model performance on the hold-out test data with various evaluation metrics. 2xlarge instances, so you should raise a service limit increase request if your account requires increased limits for this type. This notebook demonstrates how to use the JumpStart API for text classification. Training uses five ml.g4dn.2xlarge

Scripts 69

Scripts Metrics APIs Healthcare 69

AWS Machine Learning

OCTOBER 19, 2022

To demonstrate how you can use this solution in your existing business infrastructures, we also include an example of making REST API calls to the deployed model endpoint, using AWS Lambda to trigger both the RCF and XGBoost models. If you don’t have an account, you can sign up for one. Prerequisites. Launch the solution. ROC AUC. –.

APIs 65

APIs Metrics Calibration Accountability 65

AWS Machine Learning

FEBRUARY 12, 2024

Client package development – A client package was developed that acts as a wrapper around SageMaker APIs and the previously existing code. For hyperparameter tuning, a hyperparameter optimization (HPO) job can be initiated, selecting the best model based on the objective metric. The evaluation report is then stored in Amazon S3.

Engineering 103

Engineering Wait times Metrics Accountability 103

AWS Machine Learning

NOVEMBER 1, 2023

However, like other nascent technologies, obstacles remain in managing model intricacy, harmonizing diverse modalities, and formulating uniform evaluation metrics. The TGI framework underpins the model inference layer, providing RESTful APIs for robust integration and effortless accessibility.

APIs 87

APIs Engineering Construction Scripts 87

AWS Machine Learning

SEPTEMBER 18, 2023

Each stage in the ML workflow is broken into discrete steps, with its own script that takes input and output parameters. In the following code, the desired number of actors is passed in as an input argument to the script. Let’s look at sections of the scripts that perform this data preprocessing. get("OfflineStoreConfig").get("S3StorageConfig").get("ResolvedOutputS3Uri")

Scripts 93

Scripts APIs Government Construction 93

AWS Machine Learning

NOVEMBER 16, 2022

Enhanced monitoring and observability for ML workloads including Amazon EKS, Kubeflow metrics, and application logs using Prometheus, Grafana, and Amazon CloudWatch integrations. Automated deployment options have been improved and simplified using Kustomize scripts and Helm charts. Kubeflow on AWS 1.6.1 and PyTorch 1.12.1.

Metrics 65

Metrics Scripts Enterprise APIs 65

AWS Machine Learning

JULY 3, 2023

This includes scripts for model loading, inference handling etc. Then, using the SageMaker API, we can start the asynchronous inference job as follows: import glob import time max_images = 10 input_locations,output_locations, = [], [] for i, file in enumerate(glob.glob("data/processedimages/*.png")):

APIs 78

APIs Calibration Scripts Automotive 78

AWS Machine Learning

MARCH 20, 2023

Use the supplied Python scripts for quantization. Run the provided Python test scripts to invoke the SageMaker endpoint for both INT8 and FP32 versions. Quantizing the model in PyTorch is possible with a few APIs from Intel PyTorch extensions. py scripts for testing. times greater with INT8 quantization.

Calibration 76

Calibration Scripts Benchmark APIs 76

AWS Machine Learning

JULY 14, 2022

This post walks you through an example of how to track your experiments across code, data, artifacts, and metrics by using Amazon SageMaker Experiments in conjunction with Data Version Control (DVC). In each individual experiment, we track input and output artifacts, code, and metrics using SageMaker Experiments. SageMaker Experiments.

Scripts 74

Scripts Engineering Metrics APIs 74

AWS Machine Learning

JUNE 6, 2023

Run your DLC container with a model training script to fine-tune the RoBERTa model. After model training is complete, package the saved model, inference scripts, and a few metadata files into a tar file that SageMaker inference can use and upload the model package to an Amazon Simple Storage Service (Amazon S3) bucket.

Scripts 67

Scripts APIs Benchmark Management 67

AWS Machine Learning

OCTOBER 11, 2022

It provides APIs powered by ML to extract key phrases, entities, sentiment analysis, and more. You also need an AWS account and the ability to create AWS resources. For this demo, you should have the following prerequisites: An AWS account. The code for this solution is available on Github. Prerequisites. Python 3.7 LTS version.

APIs 70

APIs Enterprise Engineering Accountability 70

AWS Machine Learning

DECEMBER 6, 2023

Another driver behind RAG’s popularity is its ease of implementation and the existence of mature vector search solutions, such as those offered by Amazon Kendra (see Amazon Kendra launches Retrieval API ) and Amazon OpenSearch Service (see k-Nearest Neighbor (k-NN) search in Amazon OpenSearch Service ), among others.

Analytics 95

Analytics APIs Engineering Construction 95

AWS Machine Learning

AUGUST 11, 2022

For example, in some e-commerce platforms, account registration is wide open. Fraudsters can behave maliciously just once with an account and never use the same account again. Additionally, it’s challenging to construct a streaming data pipeline that can feed incoming events to a GNN real-time serving API.

Construction 81

Construction APIs Accountability Scripts 81

AWS Machine Learning

NOVEMBER 20, 2023

Retrieval Augmented Generation (RAG) allows you to provide a large language model (LLM) with access to data from external knowledge sources such as repositories, databases, and APIs without the need to fine-tune it. If you are new to AWS, see Create a standalone AWS account. Llama 2 7b chat is available under the Llama 2 license.

APIs 90

APIs Entertainment Accountability Customer Experience 90

AWS Machine Learning

MAY 9, 2023

Inference requests arrive at the server via either HTTP/REST or by the C API and are then routed to the appropriate per-model scheduler. SageMaker MMEs offer capabilities for running multiple deep learning or ML models on the GPU at the same time with Triton Inference Server, which has been extended to implement the MME API contract.

APIs 78

APIs Scripts Best practices Enterprise 78

AWS Machine Learning

MAY 30, 2023

You can also apply additional filters such as account number, EC2 instance type, cost allocation tag, Region, and more. Optionally, you can enable AWS Cost and Usage Reports (AWS CUR) to gain insights into the cost and usage data for your accounts. For a full list of metrics, refer to Monitor Amazon SageMaker with Amazon CloudWatch.

Best practices 66

Best practices Metrics Accountability APIs 66