AWS Machine Learning

SEPTEMBER 20, 2023

For example, you may want to make use of Amazon SageMaker to build and train ML model, or use Amazon SageMaker Jumpstart to deploy pre-built foundation or third party ML models, which you can deploy at the click of a few buttons. We show how you can build and train an ML model in AWS and deploy the model in another platform.

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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.

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Scripts Call Center Telemarketing Best practices 98

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.

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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.

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Scripts Metrics Healthcare Accountability 91

AWS Machine Learning

FEBRUARY 13, 2024

Features are inputs to ML models used during training and inference. Also, when features used to train models offline in batch are made available for real-time inference, it’s hard to keep the two feature stores synchronized. For a deep dive, refer to Cross account feature group discoverability and access.

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AWS Machine Learning

NOVEMBER 15, 2024

For early detection, implement custom testing scripts that run toxicity evaluations on new data and model outputs continuously. Integrating scheduled toxicity assessments and custom testing scripts into your development pipeline helps you continuously monitor and adjust model behavior.

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APIs Government Best practices Metrics 111

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.

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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.

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AWS Machine Learning

FEBRUARY 12, 2025

Trained on broad, generic datasets spanning a wide range of topics and domains, LLMs use their parametric knowledge to perform increasingly complex and versatile tasks across multiple business use cases. For details, refer to Creating an AWS account. We use JupyterLab in Amazon SageMaker Studio running on an ml.t3.medium

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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.

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Contact Center Self service Banking Airlines 289

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.

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Accountability Best practices Scripts Engineering 97

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.

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Scripts Best practices Engineering Management 118

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.

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Best practices Call Center Outbound sales Telemarketing 182

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).

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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.

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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.

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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?

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Scripts Accountability Transportation Benchmark 90

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.

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Customer Service Coaching Contact Center Banking 106

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.

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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.

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Scripts Accountability Best practices Engineering 122

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.

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CCNG Contact Center Scripts Feedback 195

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.

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Scripts Best practices Transportation Construction 92

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.

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Best practices APIs Transportation Scripts 101

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.

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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.

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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.

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Scripts Metrics Finance Enterprise 95

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.

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APIs Scripts Real estate Accountability 125

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.

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Scripts Accountability Engineering Best practices 132

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.

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Scripts Engineering Metrics Best practices 120

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.

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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).

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APIs Scripts Best practices Management 109

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.

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Customer Service Scripts Construction Feedback 273

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.

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Telecommunications Scripts Enterprise Engineering 98

Fonolo

SEPTEMBER 16, 2021

Top 3 methods for training tone of voice. It’s essential for call center managers to take tone of voice into consideration when developing an agent training program. Here are 3 tips on how to train tone of voice to call center agents: 1. Communicate what your brand stands for throughout the training process.

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Customer Service Call Center Scripts Interactive Voice Response 167

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.

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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.

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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.

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