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These sessions, featuring Amazon Q Business , Amazon Q Developer , Amazon Q in QuickSight , and Amazon Q Connect , span the AI/ML, DevOps and Developer Productivity, Analytics, and Business Applications topics. Builders’ sessions – These highly interactive 60-minute mini-workshops are conducted in small groups of fewer than 10 attendees.
Define – Business Model Innovation / Industry Transformation, Machine 2 Machine; Augmented Decisions / Self Learning Analytics; Inventory Digital Assets; New Growth and Constant Innovation. Most importantly, workshops are customized to address the customer’s business problems, including strategy, implementation, and enablement.
The action is an API that the model can invoke from an allowed set of APIs. Action groups are mapped to an AWS Lambda function and related API schema to perform API calls. Customers converse with the bot in natural language with multiple steps invoking external APIs to accomplish subtasks.
Workshops – In these hands-on learning opportunities, in the course of 2 hours, you’ll be able to build a solution to a problem, and understand the inner workings of the resulting infrastructure and cross-service interaction. Bring your laptop and be ready to learn! Reserve your seat now! Reserve your seat now! Reserve your seat now!
ZOE is a multi-agent LLM application that integrates with multiple data sources to provide a unified view of the customer, simplify analytics queries, and facilitate marketing campaign creation. From our experience, artifact server has some limitations, such as limits on artifact size (because of sending it using REST API).
In the architecture shown in the following diagram, users input text in the React -based web app, which triggers Amazon API Gateway , which in turn invokes an AWS Lambda function depending on the bias in the user text. Additionally, it highlights the specific parts of your input text related to each category of bias.
On the agenda for 2019 are the following topics: Analytics and AI; agents and automation; efficiency and effectiveness; multi-channel and omni-channel; and customer and digital experiences. The day includes a wealth of networking opportunities, roundtable discussions, and expert-led workshops. This is one is not to be missed!
Web crawler for knowledge bases With a web crawler data source in the knowledge base, you can create a generative AI web application for your end-users based on the website data you crawl using either the AWS Management Console or the API. Hardik shares his knowledge at various conferences and workshops.
And last but never least, we have exciting workshops and activities with AWS DeepRacer—they have become a signature event! Workshops – Hands-on learning opportunities where, in the course of 2 hours, you’ll be able to build a solution to a problem, understand the inner workings of the resulting infrastructure, and cross-service interaction.
The underlying technologies of composability include some combination of artificial intelligence (AI), machine learning, automation, container-based architecture, big data, analytics, low-code and no-code development, Agile/DevOps deployment, cloud delivery, and applications with open APIs (microservices).
Wipro has used the input filter and join functionality of SageMaker batch transformation API. The response is returned to Lambda and sent back to the application through API Gateway. Use QuickSight refresh dataset APIs to automate the spice data refresh. It helped enrich the scoring data for better decision making.
To classify and extract information needed to validate information in accordance with a set of configurable funding rules, Informed uses a series of proprietary rules and heuristics, text-based neural networks, and image-based deep neural networks, including Amazon Textract OCR via the DetectDocumentText API and other statistical models.
The user can use the Amazon Recognition DetectText API to extract text data from these images. Because the Python example codes were saved as a JSON file, they were indexed in OpenSearch Service as vectors via an OpenSearchVevtorSearch.fromtexts API call. About the authors Julia Hu is a Sr.
You can effectively use Snowflake Marketplace to monetize your predictive analytics from datasets produced in Amazon Forecast. In short, the service delivers all the science, data handling, and resource management into a simple API call. He has helped technology companies design and implement data analytics solutions and products.
OpenSearch is an open source and distributed search and analytics suite derived from Elasticsearch. Learn more about prompt engineering and generative AI-powered Q&A in the Amazon Bedrock Workshop. It also formats complex structures like tables for easier analysis.
We implement the RAG functionality inside an AWS Lambda function with Amazon API Gateway to handle routing all requests to the Lambda. We implement a chatbot application in Streamlit which invokes the function via the API Gateway and the function does a similarity search in the OpenSearch Service index for the embeddings of user question.
The results data from these jobs are stored in the Amazon S3 analytics layer. The Amazon S3 analytics layer is used to store the data that is used by the ML models for training purposes. The prepared training dataset is pushed to the analytics S3 bucket to be used by SageMaker. Train the model.
For example, the analytics team may curate features like customer profile, transaction history, and product catalogs in a central management account. His expertise spans a broad spectrum, encompassing scalable architectures, distributed computing, big data analytics, micro services and cloud infrastructures for organizations.
You can change the configuration later from the SageMaker Canvas UI or using SageMaker APIs. To explore more about SageMaker Canvas with industry-specific use cases, explore a hands-on workshop. About the Authors Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice. Choose Deploy.
The Hugging Face transformers , tokenizers , and datasets libraries provide APIs and tools to download and predict using pre-trained models in multiple languages. Next, we can move the input tensors to the GPU used by the current process using the torch.cuda.set_device API followed by the.to() API call.
He designs modern application architectures based on microservices, serverless, APIs, and event-driven patterns. He works with customers to realize their data analytics and machine learning goals through adoption of DataOps and MLOps practices and solutions. Machine Learning Solutions Architect based in Florida, US.
The financial services industry (FSI) is no exception to this, and is a well-established producer and consumer of data and analytics. This mostly non-technical post is written for FSI business leader personas such as the chief data officer, chief analytics officer, chief investment officer, head quant, head of research, and head of risk.
If you have challenges in fully defining your specific customer support needs, consider partnering with a development company that can help you articulate your chatbot requirements through stakeholder workshops. Pre-built templates and seamless integrations also ease setup. Prioritize capabilities that directly address your priorities.
The underlying technologies of composability include some combination of artificial intelligence (AI), machine learning, automation, container-based architecture, big data, analytics, low-code and no-code development, Agile/DevOps deployment, cloud delivery, and applications with open APIs (microservices).
These systems help route calls to the appropriate agents, track customer interactions, manage customer data, and provide analytics for monitoring and improving performance. They do not support advanced features such as call recording, analytics, or seamless integration with customer relationship management (CRM) tools.
6 Onboarding and Support Enterprise contact center software provides personalized onboarding, training and workshops, dedicated account manager, and ongoing support. 8×8 8×8 is an excellent enterprise contact center software provider that combines contact center, voice, video, chat, and enterprise API solutions.
In this post, we demonstrate how to add features to a feature group using the newly released UpdateFeatureGroup API. To update the feature group to add a new feature, we use the new Amazon SageMaker UpdateFeatureGroup API. We ingest the DataFrame into the feature group using the SageMaker SDK FeatureGroup.ingest API.
After you and your teams have a basic understanding of security on AWS, we strongly recommend reviewing How to approach threat modeling and then leading a threat modeling exercise with your teams starting with the Threat Modeling For Builders Workshop training program.
The Lambda function can be integrated with external credit APIs. Based on the instructions and the API descriptions, the Amazon Bedrock agent creates a logical sequence of steps to complete an action. Action groups define the APIs for performing actions such as creating the loan, checking the user, fetching the risk score, and so on.
Security analytics can then be performed against the transcripts, enabling organizations to improve their security posture by increasing their ability to detect security anomalies by bad actors. The UI is provided by a simple Streamlit application with access to the DynamoDB and Amazon Bedrock APIs.
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