For a long time, I thought I was doing everything right. I tracked everything — workouts, calories, sleep, water intake, even alcohol consumption and reading habits. Like many people, I relied on Apple Health to store all my data. The problem wasn’t collecting the data. It was understanding it. The Problem With Tracking Everything I … Continue reading Scratching My Own Itch: Turning Apple Health Data Into Insights
Integrating with AWS Lake Formation allows third-party services to securely access data stored in Amazon S3–based data lakes. Over the past few days, I’ve gained several valuable insights from hands-on experience that I’d like to share. I will walk you through the end-to-end workflow illustrated above and highlight some key lessons and challenges encountered along … Continue reading Understanding how third-party query engines integrate with Lake Formation
AWS re:Invent 2024, Amazon Web Services' flagship conference, has once again proven to be a cornerstone event in the cloud computing industry. This year's event, held in Las Vegas, showcased groundbreaking innovations and strategic directions that will shape the future of cloud technology. Key Highlights from the Conference The event kicked off with powerful keynotes … Continue reading [AI Generated] AWS re:Invent 2024: Key Highlights and Game-Changing Announcements
I deployed HuggingFace zephyr-7b-beta model to SageMaker by using the default deploy.py script. When trying to invoke the model endpoint, I received the error "ValueError: Error raised by inference endpoint: An error occurred (ModelError) when calling the InvokeEndpoint operation: Received client error (422) from primary with message "{"error":"Input validation error: inputs must have less than … Continue reading Increase max input length for HuggingFace model in SageMaker deployment
AWS CodeGuru is a developer tool that provides intelligent recommendations to improve code quality and identify an application’s most expensive lines of code.
Jackie Chen's IT Workshop 