AWS Machine Learning

JUNE 9, 2022

SageMaker JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as well as a selection of end-to-end solutions that solve common business problems. In this post, we’re excited to announce that all trainable JumpStart models now support incremental training.

Scripts 96

Scripts APIs Enterprise Accountability 96

CCNG

JUNE 7, 2023

Language Support : Chat GPT can be trained in multiple languages, enabling contact centers to provide support to customers globally without the need for multilingual agents. In the end, writing scripts, using it for marketing or content and other simple tasks appear to be the main use cases right now.” says Fred.

Contact Center 195

Contact Center CCNG APIs Scripts 195

AWS Machine Learning

APRIL 19, 2024

In this post, we focus on how we used Karpenter on Amazon Elastic Kubernetes Service (Amazon EKS) to scale AI training and inference, which are core elements of the Iambic discovery platform. We wanted to build a scalable system to support AI training and inference. The service is exposed behind a reverse-proxy using Traefik.

Metrics 123

Metrics APIs Scripts Construction 123

AWS Machine Learning

JULY 29, 2022

Pre-trained models and fully managed NLP services have democratised access and adoption of NLP. Amazon SageMaker is a fully managed service that provides developers and data scientists the ability to build, train, and deploy machine learning (ML) models quickly. Build your training script for the Hugging Face SageMaker estimator.

Scripts 101

Scripts APIs Big data Engineering 101

AWS Machine Learning

MARCH 15, 2023

The best practice for migration is to refactor these legacy codes using the Amazon SageMaker API or the SageMaker Python SDK. SageMaker runs the legacy script inside a processing container. Step Functions is a serverless workflow service that can control SageMaker APIs directly through the use of the Amazon States Language.

Scripts 144

Scripts APIs Engineering Construction 144

AWS Machine Learning

DECEMBER 22, 2023

Large language model (LLM) training has surged in popularity over the last year with the release of several popular models such as Llama 2, Falcon, and Mistral. Training performant models at this scale can be a challenge. These features improve the usability of the library, expand functionality, and accelerate training.

Scripts 119

Scripts APIs Engineering Finance 119

AWS Machine Learning

FEBRUARY 16, 2023

Modern model pre-training often calls for larger cluster deployment to reduce time and cost. At the server level, such training workloads demand faster compute and increased memory allocation. As models grow to hundreds of billions of parameters, they require a distributed training mechanism that spans multiple nodes (instances).

Scripts 101

Scripts APIs Benchmark Engineering 101

AWS Machine Learning

OCTOBER 31, 2022

Training these gigantic models is challenging and requires complex distribution strategies. Data scientists and machine learning engineers are constantly looking for the best way to optimize their training compute, yet are struggling with the communication overhead that can increase along with the overall cluster size. on 256 GPUs.

Scripts 94

Scripts Benchmark APIs Engineering 94

AWS Machine Learning

MAY 16, 2024

The main AWS services used are SageMaker, Amazon EMR , AWS CodeBuild , Amazon Simple Storage Service (Amazon S3), Amazon EventBridge , AWS Lambda , and Amazon API Gateway. The SageMaker pipeline predefined in CodeBuild runs, and sequentially runs steps such as preprocessing including provisioning, model training, and model registration.

Personalization 124

Personalization APIs Scripts Technical Support 124

AWS Machine Learning

MARCH 6, 2023

Large language models (LLMs) are neural network-based language models with hundreds of millions ( BERT ) to over a trillion parameters ( MiCS ), and whose size makes single-GPU training impractical. The size of an LLM and its training data is a double-edged sword: it brings modeling quality, but entails infrastructure challenges.

Best practices 105

Best practices APIs Transportation Scripts 105

AWS Machine Learning

AUGUST 1, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API. The scripts for fine-tuning and evaluation are available on the GitHub repository.

APIs 124

APIs Scripts Real estate Accountability 124

Zingtree

MAY 3, 2018

If you’re a Zendesk user in a Contact Center environment, you’ll want to be using our Zendesk Agent Scripting app. This makes it easy to guide, train and onboard agents and is a huge productivity booster for everyone. This two-minute video shows you how Agents interact with the Agent Scripting App: Getting Started.

Scripts 67

Scripts APIs Feedback Contact Center 67

AWS Machine Learning

AUGUST 3, 2023

As machine learning (ML) becomes increasingly prevalent in a wide range of industries, organizations are finding the need to train and serve large numbers of ML models to meet the diverse needs of their customers. Training and serving thousands of models requires a robust and scalable infrastructure, which is where Amazon SageMaker can help.

APIs 98

APIs Scripts SaaS Management 98

AWS Machine Learning

OCTOBER 27, 2022

Certain machine learning (ML) workloads, such as training computer vision models or reinforcement learning, often involve combining the GPU- or accelerator-intensive task of neural network model training with the CPU-intensive task of data preprocessing, like image augmentation. This post is co-written with Chaim Rand from Mobileye.

Scripts 97

Scripts Benchmark Metrics Transportation 97

AWS Machine Learning

AUGUST 2, 2024

Traditionally, earnings call scripts have followed similar templates, making it a repeatable task to generate them from scratch each time. On the other hand, generative artificial intelligence (AI) models can learn these templates and produce coherent scripts when fed with quarterly financial data.

Engineering 130

Engineering Scripts Metrics APIs 130

AWS Machine Learning

OCTOBER 24, 2022

The plentiful and jointly trained parameters of DL models have a large representational capacity that brought improvements in numerous customer use cases, including image and speech analysis, natural language processing (NLP), time series processing, and more. The challenge with DL training.

Scripts 98

Scripts Enterprise APIs Benchmark 98

AWS Machine Learning

JANUARY 8, 2024

The first allows you to run a Python script from any server or instance including a Jupyter notebook; this is the quickest way to get started. In the following sections, we first describe the script solution, followed by the AWS CDK construct solution. The following diagram illustrates the sequence of events within the script.

Scripts 122

Scripts Construction APIs Healthcare 122

AWS Machine Learning

JULY 29, 2022

The data scientists in this team use Amazon SageMaker to build and train a credit risk prediction model using the shared credit risk data product from the consumer banking LoB. Build and train ML models using a data mesh architecture on AWS. Part 1: Data mesh set up and data product registration. Data exploration.

Scripts 99

Scripts Analytics Accountability Engineering 99

AWS Machine Learning

FEBRUARY 13, 2023

With the increasing use of artificial intelligence (AI) and machine learning (ML) for a vast majority of industries (ranging from healthcare to insurance, from manufacturing to marketing), the primary focus shifts to efficiency when building and training models at scale. The steps are as follows: Open AWS Cloud9 on the console.

Scripts 98

Scripts Best practices Transportation Construction 98

Zingtree

MAY 24, 2018

If you’re a Zendesk user in a Contact Center environment, you’ll want to be using our Zendesk Agent Scripting app. This makes it easy to guide, train and onboard agents and is a huge productivity booster for everyone. Benefits of the Zendesk Agent Scripting App. Installing the Agent Scripting App into Zendesk.

Scripts 61

Scripts APIs Real estate Feedback 61

AWS Machine Learning

JUNE 29, 2022

However, training these gigantic networks from scratch requires a tremendous amount of data and compute. For smaller NLP datasets, a simple yet effective strategy is to use a pre-trained transformer, usually trained in an unsupervised fashion on very large datasets, and fine-tune it on the dataset of interest. training script.

Benchmark 100

Benchmark Metrics APIs Scripts 100

AWS Machine Learning

JANUARY 5, 2024

The AWS portfolio of ML services includes a robust set of services that you can use to accelerate the development, training, and deployment of machine learning applications. Collaboration – Data scientists each worked on their own local Jupyter notebooks to create and train ML models.

Management 131

Management APIs Engineering Government 131

AWS Machine Learning

APRIL 12, 2023

In this post, we share how Games24x7 improved their training pipelines for their responsible gaming platform using Amazon SageMaker. This step-function instantiated a cluster of instances to extract and process data from S3 and the further steps of pre-processing, training, evaluation would run on a single large EC2 instance.

Scripts 107

Scripts APIs Metrics Best practices 107

AWS Machine Learning

AUGUST 3, 2023

Training ML algorithms for pose estimation requires a lot of expertise and custom training data. Therefore, we present two options: one that doesn’t require any ML expertise and uses Amazon Rekognition, and another that uses Amazon SageMaker to train and deploy a custom ML model. Both requirements are hard and costly to obtain.

APIs 92

APIs Scripts Engineering Technical Support 92

AWS Machine Learning

NOVEMBER 7, 2022

JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as well as a selection of end-to-end solutions that solve common business problems. In this post, we provide a step-by-step walkthrough on how to deploy pre-trained stable diffusion models for generating images from text.

APIs 107

APIs Scripts Enterprise Big data 107

AWS Machine Learning

JANUARY 24, 2025

Contrast that with Scope 4/5 applications, where not only do you build and secure the generative AI application yourself, but you are also responsible for fine-tuning and training the underlying large language model (LLM). These steps might involve both the use of an LLM and external data sources and APIs.

APIs 114

APIs Scripts Best practices Management 114

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 123

APIs Scripts Entertainment Personalization 123

AWS Machine Learning

NOVEMBER 7, 2022

JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as well as a selection of end-to-end solutions that solve common business problems. In this post, we provide a step-by-step walkthrough on how to deploy pre-trained text generation models.

APIs 108

APIs Scripts Enterprise Big data 108

AWS Machine Learning

JULY 11, 2024

Retrieval Augmented Generation (RAG) is a popular paradigm that provides additional knowledge to large language models (LLMs) from an external source of data that wasn’t present in their training corpus. For more information about fine tuning Sentence Transformer, see Sentence Transformer training overview.

Scripts 130

Scripts Accountability APIs Engineering 130

AWS Machine Learning

AUGUST 4, 2022

The Amazon S3 analytics layer is used to store the data that is used by the ML models for training purposes. The repricing ML model is a Scikit-Learn Random Forest implementation in SageMaker Script Mode, which is trained using data available in the S3 bucket (the analytics layer). Train the model.

Scripts 123

Scripts Advertising Engineering Analytics 123

AWS Machine Learning

MARCH 23, 2023

Although this example shows how to perform this for inference operations, you can extend the solution to training and other ML steps. Endpoints are deployed with a couple clicks or lines of code using SageMaker, which simplifies the process for developers and ML experts to build and train ML and deep learning models in the cloud.

Scripts 116

Scripts APIs Government Analytics 116

AWS Machine Learning

FEBRUARY 29, 2024

The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.

APIs 135

APIs Healthcare Scripts Enterprise 135

AWS Machine Learning

AUGUST 26, 2022

JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as well as a selection of end-to-end solutions that solve common business problems. Fine-tune pre-trained models – JumpStart allows you to fine-tune pre-trained models with no need to write your own training algorithm.

APIs 98

APIs Scripts Enterprise Big data 98

AWS Machine Learning

MAY 31, 2023

The Amazon SageMaker Python SDK is an open-source library for training and deploying machine learning (ML) models on Amazon SageMaker. In such cases, data scientists have to provide these parameters to their ML model training and deployment code manually, by noting down subnets, security groups, and KMS keys.

APIs 107

APIs Scripts Accountability Enterprise 107

AWS Machine Learning

SEPTEMBER 28, 2022

Data scientists often train their models locally and look for a proper hosting service to deploy their models. Unfortunately, there’s no one set mechanism or guide to deploying pre-trained models to the cloud. In this post, we look at deploying trained models to Amazon SageMaker hosting to reduce your deployment time.

Scripts 98

Scripts APIs Engineering Consulting 98

AWS Machine Learning

SEPTEMBER 18, 2023

This complexity often leads to the need for distributed ML, where multiple machines are used to train a single model. Ray, an open-source distributed computing framework, provides a flexible framework for distributed training and serving of ML models. SageMaker is a fully managed service for building, training, and deploying ML models.

Scripts 129

Scripts APIs Government Construction 129

AWS Machine Learning

NOVEMBER 15, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

APIs 110

APIs Government Best practices Metrics 110