AWS Machine Learning

DECEMBER 7, 2022

The success of any machine learning (ML) pipeline depends not just on the quality of model used, but also the ability to train and iterate upon this model. However, doing this tuning manually can often be cumbersome due to the size of the search space, sometimes involving thousands of training iterations. Solution overview.

Scripts 101

Scripts Metrics Healthcare Accountability 101

AWS Machine Learning

NOVEMBER 30, 2023

Building foundation models (FMs) requires building, maintaining, and optimizing large clusters to train models with tens to hundreds of billions of parameters on vast amounts of data. Customers such as Stability AI use SageMaker HyperPod to train their foundation models, including Stable Diffusion.

Scripts 131

Scripts Engineering Government Management 131

AWS Machine Learning

SEPTEMBER 18, 2024

It is important to consider the massive amount of compute often required to train these models. When using compute clusters of massive size, a single failure can often throw a training job off course and may require multiple hours of discovery and remediation from customers. In recent years, FM sizes have been increasing.

Scripts 127

Scripts Metrics Management Accountability 127

AWS Machine Learning

NOVEMBER 20, 2023

This vision model developed by KT relies on a model pre-trained with a large amount of unlabeled image data to analyze the nutritional content and calorie information of various foods. The teacher model remains unchanged during KD, but the student model is trained using the output logits of the teacher model as labels to calculate loss.

Scripts 130

Scripts Finance Telecommunications Enterprise 130

Quality Contact Solutions

JULY 26, 2022

After writing over one thousand call center scripts, we know that there isn’t a single stand-alone ingredient we’d consider the ‘secret sauce’ for creating the perfect script. Instead, scripts are purposeful and serve as a guide to accomplish the objective of the call. No, it doesn’t.

Scripts 98

Scripts Call Center Telemarketing Best practices 98

AWS Machine Learning

MAY 1, 2024

It comes in a range of parameter sizes—7 billion, 13 billion, and 70 billion—as well as pre-trained and fine-tuned variations. Many practitioners fine-tune or pre-train these Llama 2 models with their own text data to improve accuracy for their specific use case.

Scripts 129

Scripts Best practices Engineering Management 129

AWS Machine Learning

NOVEMBER 14, 2024

For a multi-account environment, you can track costs at an AWS account level to associate expenses. A combination of an AWS account and tags provides the best results. For multiple accounts, assign mandatory tags to each one, identifying its purpose and the owner responsible.

Government 118

Government Best practices Accountability APIs 118

ShepHyken

JUNE 28, 2019

With the right training, they can, and the humans will continue to do the jobs that AI isn’t ready to handle. A superagent will be a fast consumer of data and information, making them contextually aware of customer situations — and never needing to rely on a prepackaged script. Fewer phone calls, but more complex conversations.

Contact Center 297

Contact Center Self service Banking Airlines 297

AWS Machine Learning

NOVEMBER 16, 2022

When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to isolate resources, contain security threats and simplify billing-and data science pipelines are no different. Some things to note in the preceding architecture: Accounts follow a principle of least privilege to follow security best practices.

Accountability 98

Accountability Best practices Scripts Engineering 98

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 105

Scripts Benchmark APIs Engineering 105

Callminer

SEPTEMBER 23, 2020

Outbound call centers depend on skilled and well-trained agents as much as useful software to consistently meet business goals. Call centers that implement agent performance management solutions equip their agents with the ongoing coaching and training needed to perform at their best. Aim to connect.

Best practices 182

Best practices Call Center Outbound sales Telemarketing 182

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 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. Data exploration.

Scripts 101

Scripts Analytics Accountability Engineering 101

AWS Machine Learning

AUGUST 22, 2023

Many ML algorithms train over large datasets, generalizing patterns it finds in the data and inferring results from those patterns as new unseen records are processed. Native support for distributed training is offered through the Amazon SageMaker SDK, along with example notebooks in popular frameworks. What is federated learning?

Scripts 95

Scripts Accountability Transportation Benchmark 95

AWS Machine Learning

NOVEMBER 9, 2023

We build a model to predict the severity (benign or malignant) of a mammographic mass lesion trained with the XGBoost algorithm using the publicly available UCI Mammography Mass dataset and deploy it using the MLOps framework. After it’s trained, the model is registered into the central model registry to be approved by a model approver.

Scripts 131

Scripts Accountability Best practices Engineering 131

AWS Machine Learning

FEBRUARY 29, 2024

The framework code and examples presented here only cover model training pipelines, but can be readily extended to batch inference pipelines as well. Configuration files (YAML and JSON) allow ML practitioners to specify undifferentiated code for orchestrating training pipelines using declarative syntax.

Scripts 131

Scripts Engineering Metrics Best practices 131

Callminer

JANUARY 18, 2021

Use call recordings and ongoing training to nurture emotional competence among agents. Training agents to excel at their positions falls largely on teaching them to calmly coax positive results from negative situations. Emotional intelligence can be trained most effectively by refocusing your agents’ attention on their own behaviors.

Best practices 226

Best practices Call Center Contact Center Scripts 226

CCNG

JUNE 7, 2023

Handling Basic Inquiries : Chat GPT can assist with basic inquiries such as order status, account information, shipping details, or product specifications. 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.

Contact Center 195

Contact Center CCNG APIs Scripts 195

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 114

Best practices APIs Transportation Scripts 114

Integrity Solutions

SEPTEMBER 28, 2023

Their emphasis customer service training delivers end-to-end service excellence that is driving strong loyalty, competitive differentiation and direct revenue generation. They don’t want ten minutes of on-hold music only to hear canned, scripted responses that ignore their real issues and needs. Customers want empathy.

Customer Service 106

Customer Service Coaching Contact Center Banking 106

AWS Machine Learning

OCTOBER 18, 2024

SageMaker is an excellent choice for model training, because it reduces the time and cost to train and tune ML models at scale without the need to manage infrastructure. Because you pay only for what you use, you can manage your training costs more effectively. The final model artifact is saved to an S3 bucket.

Scripts 105

Scripts APIs Engineering Marketing 105

CCNG

APRIL 27, 2022

I thought about the warehouse full of employees that were waiting to ship out orders the contact center teams took, and I thought about the dozens of account managers that were depending on the contact center teams to sell products and make their clients happy. This company didn’t even have a training department.

CCNG 195

CCNG Contact Center Scripts Feedback 195

AWS Machine Learning

MARCH 6, 2024

Similarly, pLMs are pre-trained on large protein sequence databases using unlabeled, self-supervised learning. This means that it can take a long time to train them to sufficient accuracy. Long training times, plus large instances, equals high cost, which can put this work out of reach for many researchers.

Scripts 132

Scripts Biotechnology Healthcare Accountability 132

AWS Machine Learning

JUNE 17, 2024

This post outlines the steps AWS and Twilio took to migrate Twilio’s existing machine learning operations (MLOps), the implementation of training models, and running batch inferences to Amazon SageMaker. The training data used for this pipeline is made available through PrestoDB and read into Pandas through the PrestoDB Python client.

Scripts 131

Scripts Engineering Metrics Big data 131

AWS Machine Learning

AUGUST 1, 2024

The complete flow is shown in the following figure and it covers the following steps: The user invokes a SageMaker training job to fine-tune the model using QLoRA and store the weights in an Amazon Simple Storage Service (Amazon S3) bucket in the user’s account. This copy will remain until the custom model is deleted.

APIs 133

APIs Scripts Real estate Accountability 133

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 96

Scripts Best practices Transportation Construction 96

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 136

Scripts Accountability APIs Engineering 136

AWS Machine Learning

AUGUST 24, 2023

Today, we’re pleased to announce the preview of Amazon SageMaker Profiler , a capability of Amazon SageMaker that provides a detailed view into the AWS compute resources provisioned during training deep learning models on SageMaker. You also need to add domain user profiles for individual users to access the SageMaker Profiler UI application.

Scripts 97

Scripts Metrics Finance Enterprise 97

AWS Machine Learning

JUNE 4, 2024

Amazon Bedrock supports two methods of model customization: Fine-tuning allows you to increase model accuracy by providing your own task-specific labeled training dataset and further specialize your FMs. We then create an Amazon Bedrock custom model using fine-tuning, and create a second model using continued pre-training.

Scripts 137

Scripts Accountability Engineering Best practices 137

AWS Machine Learning

NOVEMBER 15, 2023

Understanding up front which preprocessing techniques and algorithm types provide best results reduces the time to develop, train, and deploy the right model. large for training job usage and Number of instances across all training jobs. AWS allows by default only 20 parallel SageMaker training jobs for both quotas.

Scripts 127

Scripts Best practices Accountability Engineering 127

AWS Machine Learning

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts. Mitigation strategies : Implementing measures to minimize or eliminate risks.

Government 111

Government Management APIs Accountability 111

AWS Machine Learning

DECEMBER 5, 2024

These organizations are engaging in both pre-training and fine-tuning massive LLMs, with parameter counts in the billions. In this post, we demonstrate how you can address this requirement by using Amazon SageMaker HyperPod training plans , which can bring down your training cluster procurement wait time.

APIs 109

APIs Engineering Scripts Wait times 109

AWS Machine Learning

APRIL 7, 2023

To reduce the barrier to entry of ML at the edge, we wanted to demonstrate an example of deploying a pre-trained model from Amazon SageMaker to AWS Wavelength , all in less than 100 lines of code. As our sample workload, we deploy a pre-trained model from Amazon SageMaker JumpStart. The following diagram illustrates this architecture.

Telecommunications 105

Telecommunications Scripts Enterprise Engineering 105

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 104

Benchmark Metrics APIs Scripts 104

AWS Machine Learning

OCTOBER 28, 2024

A preprocessor script is a capability of SageMaker Model Monitor to preprocess SageMaker endpoint data capture before creating metrics for model quality. However, even with a preprocessor script, you still face a mismatch in the designed behavior of SageMaker Model Monitor, which expects one inference payload per request.

Scripts 123

Scripts Metrics Engineering Analytics 123

Callminer

APRIL 21, 2020

Call center managers may be involved with hiring and training call center agents , monitoring call center metrics tied to agent performance , using speech analytics tools for ongoing quality monitoring , providing ongoing feedback and coaching, and more. Good scripting can lessen the amount of decision making, but another way to counteract.

Call Center 182

Call Center Management Scripts Coaching 182

AWS Machine Learning

APRIL 26, 2024

The DBRX LLM employs a fine-grained mixture-of-experts (MoE) architecture, pre-trained on 12 trillion tokens of carefully curated data and a maximum context length of 32,000 tokens. The model underwent pre-training using a dataset consisting of 12 trillion tokens of text and code. 24xlarge or ml.pde.24xlarge

Transportation 135

Transportation Scripts Accountability Benchmark 135

Callminer

APRIL 30, 2020

” – Gregory Ciotti, Go-To Scripts for Handling 10 Tricky Customer Service Scenarios , Help Scout; Twitter: @helpscout. Account for customers’ biases and try to adapt to their communication style. Companies forget this sometimes, however, and fail to adequately train representatives.

Customer Service 273

Customer Service Scripts Construction Feedback 273