Calabrio

FEBRUARY 27, 2025

Workforce Management 2025 Call Center Productivity Guide: Must-Have Metrics and Key Success Strategies Share Achieving maximum call center productivity is anything but simple. Revenue per Agent: This metric measures the revenue generated by each agent. For many leaders, it might often feel like a high-wire act.

Call Center 52

Call Center Metrics Gamification Contact Center 52

AWS Machine Learning

FEBRUARY 12, 2025

We also included a data exploration script to analyze the length of input and output tokens. For demonstration purposes, we select 3,000 samples and split them into train, validation, and test sets. You need to run the Load and prepare the dataset section of the medusa_1_train.ipynb to prepare the dataset for fine-tuning.

Scripts 77

Scripts Metrics Engineering Accountability 77

AWS Machine Learning

MARCH 27, 2025

This requirement translates into time and effort investment of trained personnel, who could be support engineers or other technical staff, to review tens of thousands of support cases to arrive at an even distribution of 3,000 per category. If the use case doesnt yield discrete outputs, task-specific metrics are more appropriate.

Education 91

Education Engineering APIs Enterprise 91

Callminer

FEBRUARY 4, 2021

Now more than ever, organizations need to actively manage the Average-Speed-of-Answer (ASA) metric. Older citizens, the unhealthy, and those in low-income areas have always been targets for social engineering. Despite the pandemic, customers have retained the expectation that if they call you, you’ll be there for them.

Call Center 345

Call Center Contact Center Finance Consulting 345

AWS Machine Learning

FEBRUARY 29, 2024

This enables data scientists to quickly build and iterate on ML models, and empowers ML engineers to run through continuous integration and continuous delivery (CI/CD) ML pipelines faster, decreasing time to production for models. You can then iterate on preprocessing, training, and evaluation scripts, as well as configuration choices.

Scripts 116

Scripts Engineering Metrics Best practices 116

AWS Machine Learning

MAY 5, 2023

To address the problems associated with complex searches, this post describes in detail how you can achieve a search engine that is capable of searching for complex images by integrating Amazon Kendra and Amazon Rekognition. A Python script is used to aid in the process of uploading the datasets and generating the manifest file.

Engineering 104

Engineering APIs Scripts Enterprise 104

AWS Machine Learning

JUNE 17, 2024

PrestoDB is an open source SQL query engine that is designed for fast analytic queries against data of any size from multiple sources. We use a preprocessing script to connect and query data from a PrestoDB instance using the user-specified SQL query in the config file. For more information on processing jobs, see Process data.

Scripts 119

Scripts Engineering Metrics Big data 119

AWS Machine Learning

OCTOBER 24, 2024

Evaluating a RAG solution Contrary to traditional machine learning (ML) models, for which evaluation metrics are well defined and straightforward to compute, evaluating a RAG framework is still an open problem. Mean Reciprocal Rank (MRR) – This metric considers the ranking of the retrieved documents.

Chatbots 85

Chatbots Metrics Scripts APIs 85

AWS Machine Learning

APRIL 1, 2024

However, training or fine-tuning these large models for a custom use case requires a large amount of data and compute power, which adds to the overall engineering complexity of the ML stack. Most of the details will be abstracted by the automation scripts that we use to run the Llama2 example. Cluster with p4de.24xlarge

Scripts 126

Scripts Engineering Metrics Management 126

AWS Machine Learning

FEBRUARY 25, 2025

Amazon Q Business only provides metric information that you can use to monitor your data source sync jobs. We recommend running similar scripts only on your own data sources after consulting with the team who manages them, or be sure to follow the terms of service for the sources that youre trying to fetch data from.

Enterprise 88

Enterprise Engineering APIs Accountability 88

Hodusoft

NOVEMBER 6, 2024

Service Level Agreements (SLAs): Ensure compliance with SLAs, which outline expected service levels and performance metrics. Identify Key Metrics and KPIs Key Performance Indicators (KPIs) are vital for measuring the success of contact center operations. This will enable you to create tailored strategies to enhance overall experience.

Best practices 52

Best practices Contact Center Contact center software Abandon rate 52

AWS Machine Learning

OCTOBER 23, 2023

This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. The system is developed by a team of dedicated applied machine learning (ML) scientists, ML engineers, and subject matter experts in collaboration between AWS and Talent.com.

Engineering 112

Engineering Metrics Scripts Construction 112

AWS Machine Learning

SEPTEMBER 18, 2024

Reusable scaling scripts for rapid experimentation – HyperPod offers a set of scalable and reusable scripts that simplify the process of launching multiple training runs. The Observability section of this post goes into more detail on which metrics are exported and what the dashboards look like in Amazon Managaed Grafana.

Scripts 110

Scripts Metrics Management Accountability 110

AWS Machine Learning

OCTOBER 2, 2023

We can follow a simple three-step process to convert an experiment to a fully automated MLOps pipeline: Convert existing preprocessing, training, and evaluation code to command line scripts. Use the scripts created in step one as part of the processing and training steps. Integrate the pipeline into your CI/CD workflow.

Scripts 116

Scripts Construction Engineering APIs 116

AWS Machine Learning

MAY 29, 2024

bin/bash # Set the prompt and model versions directly in the command deepspeed /root/LLaVA/llava/train/train_mem.py --deepspeed /root/LLaVA/scripts/zero2.json It sets up a SageMaker training job to run the custom training script from LLaVA. He has over a decade experience in the FinTech industry as software engineer.

Scripts 127

Scripts Healthcare Metrics Finance 127

AWS Machine Learning

JUNE 27, 2023

This post explains how Provectus and Earth.com were able to enhance the AI-powered image recognition capabilities of EarthSnap, reduce engineering heavy lifting, and minimize administrative costs by implementing end-to-end ML pipelines, delivered as part of a managed MLOps platform and managed AI services.

Engineering 114

Engineering APIs Scripts Entertainment 114

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. Query training results: This step calls the Lambda function to fetch the metrics of the completed training job from the earlier model training step.

Management 131

Management APIs Engineering Government 131

NobelBiz

JULY 11, 2022

Scripts are an essential component of every contact center. The correct amount of data and accurate information delivery can yield impressive scripting capabilities. To provide a better customer experience (CX), dynamic agent scripting is required. Table of Contents show What is call center Dynamic Agent Scripting?

Scripts 52

Scripts Call Center Customer Experience Average Handle Time 52

AWS Machine Learning

NOVEMBER 22, 2023

Training script Before starting with model training, we need to make changes to the training script to make it XLA compliant. We followed the instructions provided in the Neuron PyTorch MLP training tutorial to add XLA-specific constructs in our training scripts. These code changes are straightforward to implement.

Scripts 112

Scripts Engineering Best practices Construction 112

AWS Machine Learning

MARCH 9, 2023

As machine learning (ML) models have improved, data scientists, ML engineers and researchers have shifted more of their attention to defining and bettering data quality. The PyTorch estimator from the sagemaker.pytorch package allows us to run our own training script in a managed PyTorch container.

Scripts 92

Scripts Engineering Metrics Management 92

AWS Machine Learning

JULY 25, 2024

The node recovery agent is a separate component that periodically checks the Prometheus metrics exposed by the node problem detector. Additionally, the node recovery agent will publish Amazon CloudWatch metrics for users to monitor and alert on these events. You can see the CloudWatch NeuronHasError_DMA_ERROR metric has the value 1.

Construction 110

Construction Metrics Scripts Engineering 110

AWS Machine Learning

JULY 14, 2022

Data scientists often work towards understanding the effects of various data preprocessing and feature engineering strategies in combination with different model architectures and hyperparameters. In each individual experiment, we track input and output artifacts, code, and metrics using SageMaker Experiments. SageMaker Experiments.

Scripts 95

Scripts Engineering Metrics APIs 95

AWS Machine Learning

FEBRUARY 19, 2024

Before you can write scripts that use the Amazon Bedrock API, you need to install the appropriate version of the AWS SDK in your environment. For Python scripts, you can use the AWS SDK for Python (Boto3). For more information, refer to Prompt Engineering Guidelines. exclusive) to 10.0 Parse and decode the response.

Scripts 123

Scripts APIs Entertainment Engineering 123

AWS Machine Learning

JANUARY 19, 2024

The concepts illustrated in this post can be applied to applications that use PLM features, such as recommendation systems, sentiment analysis, and search engines. The performance of the architecture is typically measured using metrics such as validation loss. training.py ).

Metrics 120

Metrics Scripts Benchmark Enterprise 120

AWS Machine Learning

APRIL 19, 2024

Solution overview In this section, we present a generic architecture that is similar to the one we use for our own workloads, which allows elastic deployment of models using efficient auto scaling based on custom metrics. The reverse proxy collects metrics about calls to the service and exposes them via a standard metrics API to Prometheus.

Metrics 122

Metrics APIs Scripts Construction 122

AWS Machine Learning

FEBRUARY 12, 2024

For hyperparameter tuning, a hyperparameter optimization (HPO) job can be initiated, selecting the best model based on the objective metric. Evaluate – A PySpark processing job evaluates the model using a custom Spark script. This decision is based on a condition metric defined in the configuration file.

Engineering 131

Engineering Wait times Metrics Accountability 131

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. Amazon Athena is a serverless SQL query engine that natively supports Iceberg management procedures. AWS Glue Job setup.

Scripts 88

Scripts Engineering APIs Big data 88

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 93

Scripts APIs Metrics Engineering 93

AWS Machine Learning

NOVEMBER 9, 2023

Under Advanced Project Options , for Definition , select Pipeline script from SCM. For Script Path , enter Jenkinsfile. upload_file("pipelines/train/scripts/raw_preprocess.py","mammography-severity-model/scripts/raw_preprocess.py") s3_client.Bucket(default_bucket).upload_file("pipelines/train/scripts/evaluate_model.py","mammography-severity-model/scripts/evaluate_model.py")

Scripts 120

Scripts Accountability Best practices Engineering 120

AWS Machine Learning

APRIL 29, 2024

Metaflow overview Metaflow was originally developed at Netflix to enable data scientists and ML engineers to build ML/AI systems quickly and deploy them on production-grade infrastructure. Through Metaflow and the deployment scripts provided in this post, you should be able to get started with Trainium with ease.

APIs 121

APIs Engineering Scripts Management 121

AWS Machine Learning

AUGUST 30, 2023

For a quantitative analysis of the generated impression, we use ROUGE (Recall-Oriented Understudy for Gisting Evaluation), the most commonly used metric for evaluating summarization. This metric compares an automatically produced summary against a reference or a set of references (human-produced) summary or translation.

Healthcare 132

Healthcare APIs Scripts Metrics 132

AWS Machine Learning

FEBRUARY 13, 2024

Before moving to full-scale production, BigBasket tried a pilot on SageMaker to evaluate performance, cost, and convenience metrics. Log model training metrics. Each worker then proceeds with the forward and backward pass defined in your training script on each GPU. Copy the final model to an S3 bucket.

Engineering 124

Engineering Gamification Big data Scripts 124

AWS Machine Learning

APRIL 2, 2024

The following figure illustrates some of these metrics: source: [link] With SageMaker JumpStart, you can deploy Solar 10.7B He is pursuing his PhD in Computer and Electrical Engineering at the Korea Advanced Institute of Science and Technology (KAIST). Along with topping the Open LLM Leaderboard, Solar 10.7B

Scripts 118

Scripts Education Engineering Technology 118

AWS Machine Learning

MARCH 2, 2023

Set up an EKS cluster with a scalable file system One way to get started with Amazon EKS is aws-do-eks , which is an open-source project offering easy-to-use and configurable scripts and tools to provision EKS clusters and run distributed training jobs. script exists in a Docker image that copies data from Amazon S3 to Amazon EFS.

Scripts 91

Scripts Engineering Metrics Transportation 91

AWS Machine Learning

MAY 16, 2024

The data preprocessing batches were created by writing a shell script to run Amazon EMR through AWS Command Line Interface (AWS CLI) commands, which we registered to Airflow to run at specific intervals. as the entry point script to handle invocations. This means keeping the same PyTorch and Python versions for training and inference.

Personalization 117

Personalization APIs Scripts Technical Support 117

AWS Machine Learning

APRIL 19, 2023

Our data scientists train the model in Python using tools like PyTorch and save the model as PyTorch scripts. Ideally, we instead want to load the model PyTorch scripts, extract the features from model input, and run model inference entirely in Java. They use the DJL PyTorch engine to initialize the model predictor.

Engineering 90

Engineering APIs Scripts Education 90

AWS Machine Learning

MAY 8, 2023

To serve models, Triton supports various backends as engines to support the running and serving of various ML models for inference. With kernel auto-tuning, the engine selects the best algorithm for the target GPU, maximizing hardware utilization. Import the ONNX model into TensorRT and generate the TensorRT engine.

Engineering 98

Engineering APIs Best practices Scripts 98