AWS Machine Learning

SEPTEMBER 20, 2023

SageMaker Studio allows data scientists, ML engineers, and data engineers to prepare data, build, train, and deploy ML models on one web interface. SageMaker is a comprehensive ML service enabling business analysts, data scientists, and MLOps engineers to build, train, and deploy ML models for any use case, regardless of ML expertise.

Scripts 99

Scripts Engineering Accountability Enterprise 99

Hodusoft

APRIL 17, 2024

In this blog post, we will discuss everything about auto attendants starting from what they are, how they work, the pros and cons of using auto attendants, how to set up an auto attendant, and how to include scripts. Pros of Using Auto Attendant Cons of Auto Attendant Auto Attendant Scripts – What to Record? Read on to know more.

Real estate 52

Real estate Scripts Interactive Voice Response First call resolution 52

AWS Machine Learning

APRIL 22, 2024

Typically, HyperPod clusters are used by multiple users: machine learning (ML) researchers, software engineers, data scientists, and cluster administrators. To achieve this multi-user environment, you can take advantage of Linux’s user and group mechanism and statically create multiple users on each instance through lifecycle scripts.

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Scripts Engineering Management Benchmark 86

AWS Machine Learning

APRIL 18, 2024

Amazon Bedrock empowers teams to generate Terraform and CloudFormation scripts that are custom fitted to organizational needs while seamlessly integrating compliance and security best practices. Traditionally, cloud engineers learning IaC would manually sift through documentation and best practices to write compliant IaC scripts.

Scripts 97

Scripts Best practices Engineering Accountability 97

AWS Machine Learning

MARCH 8, 2023

After the data is downloaded into the training instance, the custom training script performs data preparation tasks and then trains the ML model using the XGBoost Estimator. Store your Snowflake account credentials in AWS Secrets Manager. Ingest the data in a table in your Snowflake account. amazonaws.com/sagemaker-xgboost:1.5-1

Scripts 105

Scripts Accountability Enterprise Management 105

AWS Machine Learning

DECEMBER 21, 2022

Amazon SageMaker Feature Store is a purpose-built feature management solution that helps data scientists and ML engineers securely store, discover, and share curated data used in training and prediction workflows. The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account.

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Scripts Engineering APIs Big data 73

AWS Machine Learning

JANUARY 9, 2023

using open source or commercial-off-the-shelf search engines, then you’re probably familiar with the inherent accuracy challenges involved in getting relevant search results. You need your search engine to be smarter so it can rank documents based on matching the meaning or semantics of the content to the intention of the user’s query.

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Scripts APIs Engineering Transportation 79

AWS Machine Learning

NOVEMBER 15, 2023

Prerequisites The following are prerequisites for completing the walkthrough in this post: An AWS account Familiarity with SageMaker concepts, such as an Estimator, training job, and HPO job Familiarity with the Amazon SageMaker Python SDK Python programming knowledge Implement the solution The full code is available in the GitHub repo.

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Scripts Best practices Accountability Engineering 87

AWS Machine Learning

JANUARY 5, 2024

Wipro further accelerated their ML model journey by implementing Wipro’s code accelerators and snippets to expedite feature engineering, model training, model deployment, and pipeline creation. Across accounts, automate deployment using export and import dataset, data source, and analysis API calls provided by QuickSight.

Management 110

Management APIs Engineering Government 110

AWS Machine Learning

APRIL 11, 2023

As long as a user has access to the AWS account, Studio domain ID, and user profile, they can access the link. Next the script will install packages iproute and jq , which will be used in the following step. Next the script will install packages iproute and jq , which will be used in the following step. sh setup.sh sh setup.sh

Scripts 73

Scripts Automotive Engineering Healthcare 73

AWS Machine Learning

JULY 29, 2022

In part 1 , we addressed the data steward persona and showcased a data mesh setup with multiple AWS data producer and consumer accounts. The workflow consists of the following components: The producer data steward provides access in the central account to the database and table to the consumer account. Data exploration.

Scripts 71

Scripts Analytics Accountability Engineering 71

AWS Machine Learning

JULY 5, 2022

Data Wrangler is a capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications via a visual interface. LCC scripts are triggered by Studio lifecycle events, such as starting a new Studio notebook. Apply the script (see below). Solution overview.

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Scripts Engineering APIs Consulting 80

AWS Machine Learning

MAY 10, 2023

Examples of such use cases include scaling up a feature engineering job that was previously tested on a small sample dataset on a small notebook instance, running nightly reports to gain insights into business metrics, and retraining ML models on a schedule as new data becomes available.

Scripts 74

Scripts Automotive Engineering Enterprise 74

AWS Machine Learning

JANUARY 17, 2023

This development approach can be used in combination with other common software engineering best practices such as automated code deployments, tests, and CI/CD pipelines. You have permissions to create and deploy AWS CDK and AWS CloudFormation resources as defined in the scripts outlined in the post. AWS CDK scripts.

Construction 75

Construction Engineering Automotive Scripts 75

AWS Machine Learning

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

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Best practices Government Engineering Accountability 122

Amity

MARCH 24, 2017

If you’re in business today with a recurring revenue model, of the biggest questions you must ask is “where are the gaps in my revenue engine?” Most companies have revenue engines that run on delicately intertwined gears of new logos, retention and upsell/cross-sell. Learning from Our Process.

Accountability 56

Accountability Engineering Metrics Upselling 56

AWS Machine Learning

FEBRUARY 13, 2024

Each worker then proceeds with the forward and backward pass defined in your training script on each GPU. In our entire partnership, AWS has set the bar on customer obsession and delivering results—working with us the whole way to realize promised benefits.” – Keshav Kumar, Head of Engineering at BigBasket.

Engineering 100

Engineering Gamification Scripts Big data 100

AWS Machine Learning

SEPTEMBER 28, 2022

Amazon SageMaker Pipelines allows data scientists and machine learning (ML) engineers to automate training workflows, which helps you create a repeatable process to orchestrate model development steps for rapid experimentation and model retraining. To follow along with this post, you need an AWS account with a Studio domain.

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Scripts Engineering APIs Management 70

AWS Machine Learning

OCTOBER 4, 2022

Developers usually test their processing and training scripts locally, but the pipelines themselves are typically tested in the cloud. From a very high level, the ML lifecycle consists of many different parts, but the building of an ML model usually consists of the following general steps: Data cleansing and preparation (feature engineering).

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Scripts Engineering Management APIs 72

AWS Machine Learning

OCTOBER 17, 2022

It is made of shell scripts that do the following based on the option. For Studio (Option A), the shell script does the following: Installs code-server on the Jupyter Server for a user profile. For SageMaker notebook instances (Option B), the shell script does the following: Installs code-server. chmod +x install-codeserver.sh./install-codeserver.sh

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Scripts Engineering Management Accountability 83

AWS Machine Learning

SEPTEMBER 1, 2023

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

Engineering 103

Engineering Accountability Construction APIs 103

AWS Machine Learning

FEBRUARY 13, 2023

An administrator can run the AWS CDK script provided in the GitHub repo via the AWS Management Console or in the terminal after loading the code in their environment. Make sure you have the credentials and permissions to deploy the AWS CDK stack into your account. The steps are as follows: Open AWS Cloud9 on the console.

Scripts 73

Scripts Best practices Transportation Construction 73

AWS Machine Learning

JUNE 15, 2022

In the subsequent sections, we use this example to demonstrate the use of hierarchical facets to narrow down search results along with step-by-step instructions you can follow to try this out in your own AWS account. If you just want to read about this feature without running it yourself, you can refer to the Python script facet-search-query.py

APIs 71

APIs Scripts Technology Engineering 71

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. Metric FP32 INT8 Exact Match 85.8751 85.5061 F1 92.0807 91.8728 The GitHub repo comes with the scripts to check the accuracy of the SQuAD dataset. py scripts for testing.

Calibration 78

Calibration Scripts Benchmark APIs 78

AWS Machine Learning

MARCH 21, 2023

It contains over 300 built-in data transformation steps to aid with feature engineering, normalization, and cleansing to transform your data without having to write any code. Be aware that running a training job will incur additional costs on your account. The function takes a configuration file as an argument.

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Scripts Banking APIs Best practices 62

AWS Machine Learning

NOVEMBER 9, 2022

In the following sections, we introduce the steps needed to prepare a model and build the TensorRT engine, prepare a Docker image, create a SageMaker endpoint, and verify the result. Prepare models and build the engine. NVIDIA provides detailed documentation describing how to generate the TensorRT engine. Launch a G4dn.2xlarge

Engineering 79

Engineering Accountability APIs Metrics 79

AWS Machine Learning

JULY 24, 2023

Clone the Github repository The GitHub repo provides all the scripts necessary to deploy models using FastAPI on NeuronCores on AWS Inferentia instances. script in the fastapi and trace-model folders use this to create Docker images. This script could be used for most models available on Hugging Face. code as the entry point.

Scripts 73

Scripts APIs Engineering Best practices 73

AWS Machine Learning

MAY 31, 2023

The steps are as follows: Launch the CloudFormation stack in your account. Prerequisites Before you get started, make sure you have an AWS account and an IAM user or role with administrator privileges. Log in to your AWS account and open the AWS CloudFormation console. Override the default configuration values.

APIs 79

APIs Scripts Accountability Enterprise 79

AWS Machine Learning

MARCH 23, 2023

We perform data exploration and feature engineering using a SageMaker notebook, and then perform model training using a SageMaker training job. At this stage, you may also need to do additional feature engineering of your dataset or integrate with different offline feature stores. resource("s3").Bucket Bucket (bucket).Object

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Scripts APIs Government Analytics 95

AWS Machine Learning

NOVEMBER 1, 2022

Data scientists need to only provide a tabular dataset and select the target column to predict, and Autopilot automatically infers the problem type, performs data preprocessing and feature engineering, selects the algorithms and training mode, and explores different configurations to find the best ML model. script creates an Autopilot job.

Scripts 77

Scripts APIs Metrics Engineering 77

Totango

AUGUST 23, 2022

Touchpoints may involve any medium you use to interact with customers, including: Search engine marketing. This may occur through encountering your brand or product through a search engine result, a search engine ad, a social media post, a video, a review on a technology website, word-of-mouth or other means. Blog content.

B2B 115

B2B Journey mapping SaaS Engineering 115

pindrop

JULY 15, 2020

Fraud in the IVR doesn’t look like account takeover or other fraudulent activities. Fraudsters use the IVR to gather and validate information , they query your IVR like you would a search engine- turning your CRM into their personal fraudster playland. Fraudsters use IVR to do surveillance on accounts to optimize their operations.

Interactive Voice Response 52

Interactive Voice Response Contact Center Engineering Accountability 52

AWS Machine Learning

MAY 10, 2023

This will contain, among other parameters, the information about the model file location, the container that will be used for the deployment, and the location of the inference script. (If Jaymin Desai is a Software Development Engineer with the Amazon SageMaker Inference team. Mohan Gandhi is a Senior Software Engineer at AWS.

Benchmark 78

Benchmark Engineering Best practices Scripts 78

NobelBiz

FEBRUARY 23, 2023

After all, if a contact file contains only names and phone numbers, your agents will have a hard time even with the most perfect call script. Far from the classical call scripts, these guides can automatically be customized based on clients’ data. It is true that the progressive dialer is far less comfortable for your agents.

Scripts 52

Scripts Telemarketing Contact Center CRM 52

NobelBiz

FEBRUARY 23, 2023

After all, if a contact file contains only names and phone numbers, your agents will have a hard time even with the most perfect call script. Far from the classical call scripts, these guides can automatically be customized based on clients’ data. It is true that the progressive dialer is far less comfortable for your agents.

Scripts 52

Scripts Telemarketing Contact Center CRM 52

AWS Machine Learning

OCTOBER 25, 2022

Model weights are available via scripts in the GitHub repository , and the MSAs are hosted by the Registry of Open Data on AWS (RODA). The MSA step in the protein folding workflow is computationally intensive and can account for a majority of the inference time. Set up the EKS cluster with an FSx for Lustre file system.

APIs 76

APIs Scripts Banking Engineering 76

AWS Machine Learning

NOVEMBER 16, 2022

Automated deployment options have been improved and simplified using Kustomize scripts and Helm charts. This script automates creation of the following AWS resources: VPCs and EKS clusters. Make sure you meet the following prerequisites: You have an AWS account. Kartik Kalamadi is a Software Development Engineer at Amazon AI.

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Metrics Scripts Enterprise APIs 67