AWS Machine Learning

DECEMBER 21, 2022

SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Customers can also access offline store data using a Spark runtime and perform big data processing for ML feature analysis and feature engineering use cases. Table formats provide a way to abstract data files as a table.

Scripts 75

Scripts Engineering APIs Big data 75

AWS Machine Learning

MARCH 23, 2023

default_bucket() upload _path = f"training data/fhe train.csv" boto3.Session().resource("s3").Bucket To see more information about natively supported frameworks and script mode, refer to Use Machine Learning Frameworks, Python, and R with Amazon SageMaker. resource("s3").Bucket Bucket (bucket).Object Object (upload path).upload

Scripts 113

Scripts APIs Government Analytics 113

AWS Machine Learning

JUNE 19, 2024

Imagine the possibilities: Quick and efficient brainstorming sessions, real-time ideation, and even drafting documents or code snippets—all powered by the latest advancements in AI. About the Authors Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice.

APIs 90

APIs Engineering Accountability Scripts 90

AWS Machine Learning

DECEMBER 18, 2023

In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution. MongoDB Atlas MongoDB Atlas is a fully managed developer data platform that simplifies the deployment and scaling of MongoDB databases in the cloud.

Finance 122

Finance APIs Analytics Scripts 122

AWS Machine Learning

MARCH 15, 2024

Create an MLOps deployment package As a part of the FedML documentation, we need to create the client and server packages, which the MLOps platform will distribute to the server and clients to begin training. To create these packages, run the following script found in the root directory: /build_mlops_pkg.sh

Healthcare 112

Healthcare Big data Engineering Accountability 112

TechSee

DECEMBER 5, 2017

TechSee’s technology combines AI with deep machine learning, proprietary algorithms, and Big Data to deliver a scalable cognitive system that becomes smarter with every customer support interaction. In addition, Product Managers can access reports to help design better products and support documents.

Contact Center 116

Contact Center Technology Self service Call Center 116

AWS Machine Learning

AUGUST 8, 2023

Amazon SageMaker offers several ways to run distributed data processing jobs with Apache Spark, a popular distributed computing framework for big data processing. install-scripts chmod +x install-history-server.sh./install-history-server.sh script and attach it to an existing SageMaker Studio domain.

Scripts 69

Scripts Engineering Big data Management 69

AWS Machine Learning

MARCH 22, 2023

Register the Data Wrangler application within the IdP Refer to the following documentation for the IdPs that Data Wrangler supports: Azure AD Okta Ping Federate Use the documentation provided by your IdP to register your Data Wrangler application. bin/bash set -eux ## Script Body cat > ~/.snowflake_identity_provider_oauth_config

APIs 82

APIs Engineering Analytics Scripts 82

AWS Machine Learning

JULY 25, 2022

For detailed instructions on how to use the DGL-KE, refer to Training knowledge graph embeddings at scale with the Deep Graph Library and DGL-KE Documentation. SageMaker processing allows you to run a script remotely on a chosen instance type and Docker image without having to worry about resource allocation and data transfer.

Scripts 76

Scripts Engineering Analytics APIs 76

AWS Machine Learning

NOVEMBER 14, 2024

For example, a use case that’s been moved from the QA stage to pre-production could be rejected and sent back to the development stage for rework because of missing documentation related to meeting certain regulatory controls. These stages are applicable to both use case and model stages. To get started, set-up a name for your experiment.

Government 87

Government Management APIs Accountability 87

AWS Machine Learning

SEPTEMBER 30, 2022

Security is a big-data problem. Its widespread use and the general perception that such documents are airtight and static have lulled users into a false sense of security. As soon as a download attempt is made, it triggers the malicious executable script to connect to the attacker’s Command and Control server.

Scripts 83

Scripts Engineering Metrics Big data 83

AWS Machine Learning

SEPTEMBER 9, 2022

In the artificial intelligence (AI) space, athenahealth uses data science and machine learning (ML) to accelerate business processes and provide recommendations, predictions, and insights across multiple services. Each project maintained detailed documentation that outlined how each script was used to build the final model.

Engineering 78

Engineering Healthcare APIs Scripts 78

AWS Machine Learning

JULY 21, 2022

As a result, this experimentation phase can produce multiple models, each created from their own inputs (datasets, training scripts, and hyperparameters) and producing their own outputs (model artifacts and evaluation metrics). At the start, the process is full of uncertainty and is highly iterative.

Metrics 80

Metrics Scripts Enterprise Telecommunications 80

aircall

JUNE 2, 2021

When you meet face-to-face, you can also securely share sensitive documents and information. Top features include screen sharing (for presentations) and on-screen collaboration (for documents). It’s also useful when you need to trace back your conversation with customers and share sensitive information and documents.

Personalization 62

Personalization Customer Service B2B Self service 62

AWS Machine Learning

MAY 8, 2023

More information can be found in the official MLflow documentation. You can use this script add_users_and_groups.py After running the script, if you check the Amazon Cognito user pool on the Amazon Cognito console, you should see the three users created. At this point, the MLflow SDK only needs AWS credentials.

APIs 73

APIs Government Accountability Scripts 73

Vistio

OCTOBER 5, 2021

And you can look at various specific areas such as data analytics, big data, being able to study patterns within data, using artificial intelligence or using machine learning to actually gather up every customer interaction, and remember the original problem and the solution. This kind of thing really helps the agents.

Contact Center 52

Contact Center Chatbots Banking Technology 52

AWS Machine Learning

JANUARY 26, 2024

Accelerate your security and AI/ML learning with best practices guidance, training, and certification AWS also curates recommendations from Best Practices for Security, Identity, & Compliance and AWS Security Documentation to help you identify ways to secure your training, development, testing, and operational environments.

Best practices 134

Best practices Government Engineering Accountability 134

AWS Machine Learning

OCTOBER 24, 2024

Large language models (LLMs) are very large deep-learning models that are pre-trained on vast amounts of data. One model can perform completely different tasks such as answering questions, summarizing documents, translating languages, and completing sentences. Data must be preprocessed to enable semantic search during inference.

Engineering 112

Engineering Scripts Big data SaaS 112