Remove Analysis Remove APIs Remove Big data Remove Scripts
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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.

APIs 115
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­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

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. You can find the sample script in GitHub.

Scripts 73
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6 Online Data Analyst Courses

JivoChat

There is where data analysis comes in, you can use the data your company has, and key performance indicators (KPIs) to indicate what path you should follow. The Data Analyst Course With the Data Analyst Course, you will be able to become a professional in this area, developing all the necessary skills to succeed in your career.

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Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

AWS Machine Learning

Finally, we show how you can integrate this car pose detection solution into your existing web application using services like Amazon API Gateway and AWS Amplify. For each option, we host an AWS Lambda function behind an API Gateway that is exposed to our mock application. iterdir(): if p_file.suffix == ".pth":

APIs 63
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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

Define strict data ingress and egress rules to help protect against manipulation and exfiltration using VPCs with AWS Network Firewall policies. He is passionate about building secure and scalable AI/ML and big data solutions to help enterprise customers with their cloud adoption and optimization journey to improve their business outcomes.

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Fine-tune and deploy a summarizer model using the Hugging Face Amazon SageMaker containers bringing your own script

AWS Machine Learning

Amazon Comprehend is a fully managed service that can perform NLP tasks like custom entity recognition, topic modelling, sentiment analysis and more to extract insights from data without the need of any prior ML experience. Build your training script for the Hugging Face SageMaker estimator. return tokenized_dataset. to(device).

Scripts 82
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Access Snowflake data using OAuth-based authentication in Amazon SageMaker Data Wrangler

AWS Machine Learning

Access and permissions to configure IDP to register Data Wrangler application and set up the authorization server or API. For data scientist: An S3 bucket that Data Wrangler can use to output transformed data. An AWS account with permissions to create AWS Identity and Access Management (IAM) policies and roles.

APIs 79