Big data, Enterprise, Metrics and Scripts

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

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

Scripts Accountability Engineering Best practices

21 Business Analysts & Call Center Leaders Reveal the Optimal Role of the Business Analyst in Call Center Operations

Callminer

SEPTEMBER 14, 2020

For instance, to improve key call center metrics such as first call resolution , business analysts may recommend implementing speech analytics solutions to improve agent performance management. That requires involvement in process design and improvement, workload planning and metric and KPI analysis. Kirk Chewning. kirkchewning.

Call Center

Call Center Analytics First call resolution Metrics

Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

DECEMBER 21, 2022

SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Customers can also access offline store data using a Spark runtime and perform big data processing for ML feature analysis and feature engineering use cases. Table formats provide a way to abstract data files as a table.

Scripts

Scripts Engineering APIs Big data

How BigBasket improved AI-enabled checkout at their physical stores using Amazon SageMaker

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. Use SageMaker Distributed Data Parallelism (SMDDP) for accelerated distributed training. Log model training metrics. Use a custom PyTorch Docker container including other open source libraries.

Engineering

Engineering Gamification Scripts Big data

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

JANUARY 26, 2024

Reviews can be performed using tools like the AWS Well-Architected Tool , or with the help of your AWS team through AWS Enterprise Support. Define strict data ingress and egress rules to help protect against manipulation and exfiltration using VPCs with AWS Network Firewall policies.

Best practices

Best practices Government Engineering Accountability

Contact Center Trends 2021: The CX Watershed

Fonolo

NOVEMBER 17, 2020

As the focus of contact center turns to creating value rather than reducing expenses, KPIs like customer satisfaction and service level will become increasingly favored over metrics like Average Handling Time. FCR is the Most Important Metric. 2016: 50% of Global 1000 companies will have stored customer-sensitive data in the cloud.

Contact Center

Contact Center Gamification Call Center Average Handle Time

Optimizing Call Center Customer Support for Increased Revenue

Tenfold - Contact Center Blog

NOVEMBER 30, 2017

With in-depth training sessions through e-learning, virtual assistance, and scripting tools, clearly establish company goals and expectations and provide your agents the confidence to tackle any initiative. Wikibon predicted that enterprise cloud spending is growing at a 16% compound annual growth (CAGR) run rate between 2016 and 2026.

Call Center

Call Center Customer Support Customer centricity Contact Center

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning

MARCH 15, 2024

To create these packages, run the following script found in the root directory: /build_mlops_pkg.sh He entered the big data space in 2013 and continues to explore that area. Her specialization is machine learning, and she is actively working on designing solutions using various AWS ML, big data, and analytics offerings.

Healthcare

Healthcare Big data Engineering Accountability

Automate Amazon SageMaker Pipelines DAG creation

AWS Machine Learning

FEBRUARY 29, 2024

You can then iterate on preprocessing, training, and evaluation scripts, as well as configuration choices. framework/createmodel/ – This directory contains a Python script that creates a SageMaker model object based on model artifacts from a SageMaker Pipelines training step. script is used by pipeline_service.py The model_unit.py

Scripts

Scripts Engineering Metrics Best practices

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

AWS Machine Learning

AUGUST 29, 2023

Solution overview The following figure illustrates the proposed target MLOps architecture for enterprise batch inference for organizations who use GitLab CI/CD and Terraform infrastructure as code (IaC) in conjunction with AWS tools and services. The data scientist can review and approve the new version of the model independently.

Scripts

Scripts APIs Enterprise Accountability

Organize your machine learning journey with Amazon SageMaker Experiments and Amazon SageMaker Pipelines

AWS Machine Learning

JULY 21, 2022

As a result, this experimentation phase can produce multiple models, each created from their own inputs (datasets, training scripts, and hyperparameters) and producing their own outputs (model artifacts and evaluation metrics). We also illustrate how you can track your pipeline workflow and generate metrics and comparison charts.

Metrics

Metrics Scripts Enterprise Telecommunications

How Sophos trains a powerful, lightweight PDF malware detector at ultra scale with Amazon SageMaker

AWS Machine Learning

SEPTEMBER 30, 2022

Security is a big-data problem. As soon as a download attempt is made, it triggers the malicious executable script to connect to the attacker’s Command and Control server. With the built-in algorithm for XGBoost , you can do this without any additional custom script.

Scripts

Scripts Engineering Metrics Big data

Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning

MAY 8, 2023

This can be a challenge for enterprises in regulated industries that need to keep strong model governance for audit purposes. The MLflow Python SDK provides a convenient way to log metrics, runs, and artifacts, and it interfaces with the API resources hosted under the namespace /api/. You can use this script add_users_and_groups.py

APIs

APIs Government Accountability Scripts

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

AWS Machine Learning

SEPTEMBER 9, 2022

Each project maintained detailed documentation that outlined how each script was used to build the final model. In many cases, this was an elaborate process involving 5 to 10 scripts with several outputs each. For logging, we utilize FluentD to push all our container logs to Amazon OpenSearch Service and system metrics to Prometheus.

Engineering

Engineering Healthcare APIs Scripts

11 Contact Center Technologies to Boost Customer Satisfaction

TechSee

DECEMBER 5, 2017

We’ve compiled a short list of innovative customer service technologies developed by talented companies that are dedicated to helping enterprises improve their customer experience at scale and successfully compete in today’s ever-changing business environment. 1. Casengo. Servicefriend.

Contact Center

Contact Center Technology Self service Call Center

SOASTA Ushers in New Era of Innovation in Digital Performance Management

Natalie Petouhof

APRIL 4, 2016

mPulse real user monitoring (RUM) collects and analyzes 100% of the front-end performance data from every web and mobile user and correlates this data with critical business metrics – all in real time. The new SOASTA mPulse enhancements make Big Data insights easy to visualize, access and share.

Management

Management Analytics Consulting Consulting

Prepare image data with Amazon SageMaker Data Wrangler

AWS Machine Learning

MAY 1, 2023

The rapid adoption of smart phones and other mobile platforms has generated an enormous amount of image data. According to Gartner , unstructured data now represents 80–90% of all new enterprise data, but just 18% of organizations are taking advantage of this data. client('runtime.sagemaker'). alias("emb")).toPandas()

Scripts

Scripts Big data Engineering Enterprise

Customer Contact Central

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

21 Business Analysts & Call Center Leaders Reveal the Optimal Role of the Business Analyst in Call Center Operations

Trending Sources

Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

How BigBasket improved AI-enabled checkout at their physical stores using Amazon SageMaker

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

Contact Center Trends 2021: The CX Watershed

Optimizing Call Center Customer Support for Increased Revenue

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

Automate Amazon SageMaker Pipelines DAG creation

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

Organize your machine learning journey with Amazon SageMaker Experiments and Amazon SageMaker Pipelines

How Sophos trains a powerful, lightweight PDF malware detector at ultra scale with Amazon SageMaker

Securing MLflow in AWS: Fine-grained access control with AWS native services

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

11 Contact Center Technologies to Boost Customer Satisfaction

SOASTA Ushers in New Era of Innovation in Digital Performance Management

Prepare image data with Amazon SageMaker Data Wrangler

Stay Connected

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

21 Business Analysts & Call Center Leaders Reveal the Optimal Role of the Business Analyst in Call Center Operations

Trending Sources

­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

How BigBasket improved AI-enabled checkout at their physical stores using Amazon SageMaker

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

Contact Center Trends 2021: The CX Watershed

Optimizing Call Center Customer Support for Increased Revenue

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

Automate Amazon SageMaker Pipelines DAG creation

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

Organize your machine learning journey with Amazon SageMaker Experiments and Amazon SageMaker Pipelines

How Sophos trains a powerful, lightweight PDF malware detector at ultra scale with Amazon SageMaker

Securing MLflow in AWS: Fine-grained access control with AWS native services

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

11 Contact Center Technologies to Boost Customer Satisfaction

SOASTA Ushers in New Era of Innovation in Digital Performance Management

Prepare image data with Amazon SageMaker Data Wrangler

Stay Connected

Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction