AWS Machine Learning

OCTOBER 2, 2023

It is architected to automate the entire machine learning (ML) process, from data labeling to model training and deployment at the edge. In this post, we delve deep into how the labeling and model building and training parts of the pipeline are implemented. The quality of our labels will affect the quality of our ML model.

Scripts 91

Scripts Construction Engineering APIs 91

AWS Machine Learning

APRIL 8, 2024

With Knowledge Bases for Amazon Bedrock, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data using a fully managed Retrieval Augmented Generation (RAG) model. For RAG-based applications, the accuracy of the generated responses from FMs depend on the context provided to the model.

APIs 102

APIs Construction Chatbots Accountability 102

AWS Machine Learning

MARCH 25, 2024

Best practice 1 – Use data protection with Amazon Transcribe Amazon Transcribe conforms to the AWS shared responsibility model , which differentiates AWS responsibility for security of the cloud from customer responsibility for security in the cloud. Best Practice 5 – Use tag-based access control.

Best practices 79

Best practices APIs Transportation Personalization 79

Lumoa

OCTOBER 5, 2022

New incremental topic modeling. We call the process of our AI creating Topics as “Topic Modeling” The goals for the new Topic Modeling AI are: Created Topics will be more respective of users manual changes , such as manual keyword additions. We have launched a new iteration of our AI when creating Topics.

CRM 83

CRM Feedback Surveys 83

AWS Machine Learning

MAY 5, 2023

Voxel51 is the company behind FiftyOne, the open-source toolkit for building high-quality datasets and computer vision models. FiftyOne by Voxel51 is an open-source toolkit for curating, visualizing, and evaluating computer vision datasets so that you can train and analyze better models by accelerating your use cases.

Engineering 75

Engineering Feedback Marketing Management 75

AWS Machine Learning

OCTOBER 25, 2022

OpenFold, developed by Columbia University, is an open-source protein structure prediction model implemented with PyTorch. OpenFold is a faithful reproduction of the AlphaFold2 protein structure prediction model, while delivering performance improvements over AlphaFold2.

APIs 76

APIs Scripts Banking Engineering 76

AWS Machine Learning

DECEMBER 1, 2022

Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) that enables data scientists and developers to perform every step of the ML workflow, from preparing data to building, training, tuning, and deploying models. Automated tagging. Backfilling existing resources with domain tags.

APIs 66

APIs Engineering Scripts Accountability 66

AWS Machine Learning

OCTOBER 2, 2023

We show you how to use AWS IoT Greengrass to manage model inference at the edge and how to automate the process using AWS Step Functions and other AWS services. In Part 2 , we showed how to automate the labeling and model training parts of the pipeline. If you haven’t read it yet, we recommend checking out Part 1.

Engineering 88

Engineering APIs Management Enterprise 88

VirtualPBX

APRIL 2, 2024

No matter if your team operates from a traditional office, works remotely, or thrives in a hybrid model, you need a contact center solution that’s as dynamic and adaptable as your business itself. Simultaneously, streamline follow-up and analysis with Call Tagging , which automates call categorization.

contact center solutions 52

contact center solutions Contact Center CRM Analytics 52

AWS Machine Learning

FEBRUARY 13, 2024

In this post, we discuss how BigBasket used Amazon SageMaker to train their computer vision model for Fast-Moving Consumer Goods (FMCG) product identification, which helped them reduce training time by approximately 50% and save costs by 20%. To keep pace with new products, a new model was produced each month using the latest training data.

Engineering 98

Engineering Gamification Scripts Big data 98

AWS Machine Learning

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. ML operations, known as MLOps, focus on streamlining, automating, and monitoring ML models throughout their lifecycle. ML operations, known as MLOps, focus on streamlining, automating, and monitoring ML models throughout their lifecycle.

Construction 99

Construction Accountability Engineering Personalization 99

AWS Machine Learning

MARCH 6, 2024

In this post, we demonstrate how to efficiently fine-tune a state-of-the-art protein language model (pLM) to predict protein subcellular localization using Amazon SageMaker. This includes large language models (LLMs) pretrained on huge datasets, which can then be adapted for specific tasks, like text summarization or chatbots.

Scripts 91

Scripts Biotechnology Healthcare Accountability 91

AWS Machine Learning

JUNE 8, 2023

AWS Deep Learning Containers already provides pre-built Docker images for training and serving models in common frameworks such as TensorFlow, PyTorch, and MXNet. Solution overview For our example, we showcase training an image classification model using PyTorch. We use the KMNIST dataset available publicly on PyTorch.

Engineering 75

Engineering Enterprise Accountability Feedback 75

AWS Machine Learning

SEPTEMBER 29, 2022

Across almost all AWS services, SageMaker included, applying tags to resources is a standard way to track costs. These tags can help you track, report, and monitor your ML spend through out-the-box solutions like AWS Cost Explorer and AWS Budgets , as well as custom solutions built on the data from AWS Cost and Usage Reports (CURs).

Enterprise 71

Enterprise APIs Government Accountability 71

AWS Machine Learning

DECEMBER 12, 2023

This post shows you how you can create a web UI, which we call Chat Studio, to start a conversation and interact with foundation models available in Amazon SageMaker JumpStart such as Llama 2, Stable Diffusion, and other models available on Amazon SageMaker. We cover the following steps: Deploy SageMaker foundation models.

Chatbots 98

Chatbots Enterprise APIs Best practices 98

AWS Machine Learning

OCTOBER 26, 2022

Monitoring machine learning (ML) predictions can help improve the quality of deployed models. Capturing the data from inferences made in production can enable you to monitor your deployed models and detect deviations in model quality. In this solution, we send the input and the answer from the model to the extension.

APIs 104

APIs Accountability Technology Enterprise 104

Playvox

OCTOBER 20, 2022

Tag Application Method. The first step is to turn raw data (chat conversations) into information (tagged conversations). The first step is to turn raw data (chat conversations) into information (tagged conversations). Automated tagging is the ability to apply tags to conversations based on messages’ content automatically.

Feedback 59

Feedback Analytics Contact Center Surveys 59

AWS Machine Learning

AUGUST 26, 2022

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. JumpStart helps you get started with ML models for a variety of tasks without writing a single line of code.

APIs 78

APIs Scripts Enterprise Big data 78

TechSee

JANUARY 9, 2023

Computer Vision AI helped field technicians identify unfamiliar makes, models, and parts, reducing time on site and redispatch rates. lockout-tag out). Integrating Vision Through Artificial Intelligence (AI). Computer Vision AI is a technology that enables computers to see, recognize, and process images.

Technology 109

Technology Telecommunications Self service Consulting 109

Eptica

MARCH 5, 2021

Drawing on a recent webinar with Microsoft, our parent company Enghouse Interactive and Hitachi ABB Power Grids, our latest blog outlines how to understand and build the right hybrid contact centre model for the future. Read the full article here. Read the full article here.

Analytics 104

Analytics Marketing Customer Service Management 104

AWS Machine Learning

DECEMBER 1, 2022

It provides a single, web-based visual interface where you can perform all ML development steps, including preparing data and building, training, and deploying models. As an administrator you’ll only need to attach a cost allocation tag for sagemaker:space-arn. Solution overview.

Engineering 67

Engineering Personalization Management 67

Playvox

FEBRUARY 1, 2024

Ensure proper tagging. Proper tagging is essential to the accuracy of sentiment analysis. Tagging helps you categorize customer feedback and communications for better analysis and more helpful insights. Each provides important additional context and insights into customer sentiment throughout the customer journey.

Contact Center 93

Contact Center Best practices Surveys Feedback 93

AWS Machine Learning

OCTOBER 30, 2023

Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them for specific applications. For Name tag , enter bedrock-vpce. It allows developers to build and scale generative AI applications using FMs through an API, without managing infrastructure.

APIs 123

APIs Big data Accountability Enterprise 123

AWS Machine Learning

NOVEMBER 21, 2022

Amazon Comprehend is a fully managed service that enables you to build custom NLP models that are specific to your requirements, without the need for any ML expertise. For each of these NLP tasks, we demonstrate how to use Amazon SageMaker to perform the following actions: Deploy and run inference on a pre-trained model. Demo notebook.

Scripts 71

Scripts Metrics APIs Healthcare 71

AWS Machine Learning

JULY 29, 2022

Lookout for Vision now includes the ability to provide the location and type of anomalies using semantic segmentation ML models. These customized ML models can either be deployed to the AWS Cloud using cloud APIs or to custom edge hardware using AWS IoT Greengrass. Train a Lookout for Vision model in the cloud. Under HTTPS.

Scripts 69

Scripts SaaS Accountability Engineering 69

AWS Machine Learning

NOVEMBER 17, 2022

As data is growing at an exponential rate, organizations are looking to set up an integrated, cost-effective, and performant data platform in order to preprocess data, perform feature engineering, and build, train, and operationalize ML models at scale. A key component of the model building and development process is feature engineering.

Engineering 63

Engineering Big data Accountability Analytics 63

Beyond Philosophy

FEBRUARY 22, 2018

Users with iPhone 6 and 6s models (which, honestly, are not all that old!) Apple said the slowdown was intended to preserve battery life and prevent unexpected shutdowns, but critics suspected that Apple was throttling phone performance in its older models to get people to upgrade to the new iPhone x (which carries a $1000 price tag).

Consulting 326

Consulting Consulting Customer Experience 326

AWS Machine Learning

DECEMBER 1, 2022

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. Some common use cases for doing this include: Regularly running model inference to generate reports. Retraining and deploying models on some cadence. Example use case.

Engineering 72

Engineering Telecommunications Scripts Best practices 72

Peter Lavers

JULY 24, 2020

If this has been just another silo tagged on to the periphery of your business, you’re at real risk. Your best clients pre-COVID won’t necessarily remain so; what were previously 3 medium sized customers in the past could well merge and become a key account in the coming months. Digital transformation – oh, no not those words again!

B2B 130

B2B Accountability Marketing Sales 130

Beyond Philosophy

SEPTEMBER 7, 2023

Therefore, when researchers model this using data, a lot of times, it’s a weighted average of prior prices that you remember. Also, if the price tag says $10 but it’s been marked down to $8, then you compare the sale price to the regular price, which is both external reference prices. It can be almost anything.

Advertising 221

Advertising Education Sales Marketing 221

AWS Machine Learning

SEPTEMBER 23, 2022

Rekognition Custom Labels is a fully managed computer vision service that allows developers to build custom models to classify and identify objects in images that are specific and unique to their use case. A good training set is required to build an effective model using Rekognition Custom Labels. Implement the solution. Training Set.

APIs 85

APIs Metrics Management Analytics 85

AWS Machine Learning

JANUARY 17, 2023

Amazon SageMaker JumpStart is the Machine Learning (ML) hub of SageMaker providing pre-trained, publicly available models for a wide range of problem types to help you get started with machine learning. In addition to textual inputs, this model uses traditional structured data inputs such as numerical and categorical fields.

Calibration 70

Calibration Metrics Accountability Technical Support 70

CCNG

DECEMBER 20, 2023

It can instantly pull up or populate a customer profile and complete routine tasks for agents, such as filling in forms, logging details, or tagging cases. Integrating AI with RPA, especially with the addition of Generative AI and models like ChatGPT, has created an ideal scenario for using automation with machine analysis.

Call Center 195

Call Center Chatbots CCNG Technology 195

CSM Magazine

APRIL 4, 2023

The information collected can be auto-smart tagged to place it in the relevant knowledge graph with the correct taxonomy so that others can easily find and use it in the future. User-centric approach (to understand and model users) Organizations start to build infrastructure where it combines content-centric and user-centric.

Government 52

Government Engineering Enterprise Technology 52

CX Global Media

JULY 13, 2017

Eureka Starter should disrupt that thinking with a good pricing model and simplified feature set that makes it easier for smaller contact centers to extract meaningful insights from their customer conversations. You can tag calls, lists of calls, or specific sections of a transcript, for future recall and review. Full PCI Redaction.

Analytics 185

Analytics Call Center Contact Center contact center solutions 185

Interaction Metrics

JULY 10, 2023

The first step in analyzing any large unstructured dataset is called “tagging.” ” Whether you’re using AI or a team of researchers to analyze your data, the tagging process is the same – and it requires human input. Tagging is tagging. Does every comment need to be tagged?

B2B 48

B2B Customer Experience Chatbots Feedback 48

AWS Machine Learning

FEBRUARY 29, 2024

Amazon Bedrock provides a broad range of models from Amazon and third-party providers, including Anthropic, AI21, Meta, Cohere, and Stability AI, and covers a wide range of use cases, including text and image generation, embedding, chat, high-level agents with reasoning and orchestration, and more. txt) Markdown (.md) Choose Next.

APIs 111

APIs Healthcare Scripts Enterprise 111