AWS Machine Learning

AUGUST 19, 2022

Today, a lot of customers are using TensorFlow to train deep learning models for their clickthrough rate in advertising and personalization recommendations in ecommerce. Model iteration is one of a data scientist’s daily jobs, but they face the problem of taking too long to train on large datasets. Automatic mixed precision training.

Best practices 83

Best practices APIs Scripts Advertising 83

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

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 120

Metrics APIs Scripts Construction 120

AWS Machine Learning

OCTOBER 21, 2024

This feature empowers customers to import and use their customized models alongside existing foundation models (FMs) through a single, unified API. Having a unified developer experience when accessing custom models or base models through Amazon Bedrock’s API. Ease of deployment through a fully managed, serverless, service. 2, 3, 3.1,

APIs 135

APIs Scripts Finance Real estate 135

AWS Machine Learning

NOVEMBER 1, 2024

Intelligent responses and a direct conduit to Druva’s documentation – Users can gain in-depth knowledge about product features and functionalities without manual searches or watching training videos. Dru on the backend decodes log data, deciphers error codes, and invokes API calls to troubleshoot. Generate and invoke private API calls.

APIs 105

APIs Scripts Engineering Government 105

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 92

Scripts APIs Big data Engineering 92

AWS Machine Learning

OCTOBER 14, 2024

Although such multimodal models are broadly useful for answering questions and interpreting imagery, they’re limited to only answering questions based on information from their own training document dataset. This script can be acquired directly from Amazon S3 using aws s3 cp s3://aws-blogs-artifacts-public/artifacts/ML-16363/deploy.sh.

Chatbots 120

Chatbots APIs Engineering Healthcare 120

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 93

Scripts APIs Benchmark Engineering 93

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 72

Scripts APIs Enterprise Accountability 72

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 118

APIs Scripts Real estate Accountability 118

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 84

APIs Scripts SaaS Management 84

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 123

Engineering Scripts Metrics APIs 123

AWS Machine Learning

OCTOBER 15, 2024

This new SDK streamlines data processing, training, and inference and features resource chaining, intelligent defaults, and enhanced logging capabilities. In this post, we show how the SageMaker Core SDK simplifies the developer experience while providing API for seamlessly executing various steps in a general ML lifecycle.

APIs 82

APIs Construction Engineering Scripts 82

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 113

Personalization APIs Scripts Technical Support 113

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 93

Best practices APIs Transportation Scripts 93

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 70

Scripts Benchmark APIs Engineering 70

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

NOVEMBER 22, 2024

However, building or fine-tuning these pre-trained LLMs on extensive datasets demands substantial computational resources and engineering effort. Mixtral employs a sparse mixture of experts (SMoE) architecture, selectively activating only a subset of its parameters for each input during model training. QLoRA operates on a large FM.

Scripts 62

Scripts APIs Construction Engineering 62

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 75

Scripts Benchmark Metrics Transportation 75

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 131

Scripts APIs Engineering Construction 131

AWS Machine Learning

NOVEMBER 14, 2024

Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. We will start by using the SageMaker Studio UI and then by using APIs.

Government 88

Government Management APIs Accountability 88

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 84

Scripts Enterprise APIs Benchmark 84

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 104

Scripts Construction APIs Healthcare 104

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 80

Scripts Best practices Transportation Construction 80

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

NOVEMBER 19, 2024

Similarly, in tasks like code generation and suggestions through chat-based applications, users might not specify the APIs they want to use. Instead, they often request help in resolving a general issue or in generating code that utilizes proprietary APIs and SDKs. For this post, we use Meta Llama3.1

Automotive 90

Automotive Scripts APIs Engineering 90

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 67

APIs Scripts Engineering Technical Support 67

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

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 95

APIs Government Best practices Metrics 95

AWS Machine Learning

NOVEMBER 21, 2024

Fine-tuning foundation models (FMs) is a process that involves exposing a pre-trained FM to task-specific data and fine-tuning its parameters. In this post, we show how to use an Amazon SageMaker Autopilot training job with the AutoMLV2 SDK to fine-tune a Meta Llama2-7B model on question answering tasks. Check the training job status.

Metrics 82

Metrics APIs Healthcare Scripts 82

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 80

Scripts Analytics Accountability Engineering 80

AWS Machine Learning

JULY 11, 2023

With Amazon SageMaker , you can use the @remote decorator to run a SageMaker training job simply by annotating your Python code with an @remote decorator. Train a classification model based on the MNIST dataset using an @remote decorator from the open-source SageMaker Python SDK. and model.py gamma: float = 0.7,

Scripts 64

Scripts APIs Healthcare Banking 64

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 128

Management APIs Engineering Government 128

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 96

Scripts APIs Metrics Best practices 96

NobelBiz

MAY 11, 2021

Writing a call script is a must for contact centers that want to excel in their prospecting effort. If you write it according to the rules of the game, the script is an observable, cost-effective, and efficient method of attracting and maintaining prospects and clients. What exactly is call scripting? Why do scripts exist?

Scripts 52

Scripts Contact Center Calibration CRM 52

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 119

Scripts Accountability APIs Engineering 119

AWS Machine Learning

SEPTEMBER 30, 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 84

APIs Real estate Accountability Metrics 84