Remove Computer Vision Remove ML Engineer Remove Python
article thumbnail

Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 1: ModelTrainer

AWS Machine Learning Blog

Amazon SageMaker has redesigned its Python SDK to provide a unified object-oriented interface that makes it straightforward to interact with SageMaker services. Over the past 5 years, she has worked with multiple enterprise customers to set up a secure, scalable AI/ML platform built on SageMaker.

ML 99
article thumbnail

We employed ChatGPT as an ML Engineer. This is what we learned

Towards AI

We test it on a practical problem in a modality of AI in which it was not trained, computer vision, and report the results. A sensible proxy sub-question might then be: Can ChatGPT function as a competent machine learning engineer? ChatGPT’s job as our ML engineer […] improvement in precision and 34.4%

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Falcon 3 models now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

Deploying a Falcon 3 model through SageMaker JumpStart offers two convenient approaches: using the intuitive SageMaker JumpStart UI or implementing programmatically through the SageMaker Python SDK. Raghu Ramesha is a Senior ML Solutions Architect with the Amazon SageMaker Service team.

ML 85
article thumbnail

Getting Started with Docker for Machine Learning

Flipboard

Envision yourself as an ML Engineer at one of the world’s largest companies. You make a Machine Learning (ML) pipeline that does everything, from gathering and preparing data to making predictions. This is suitable for making a variety of Python applications with other dependencies being added to it at the user’s convenience.

article thumbnail

Getting Used to Docker for Machine Learning

Flipboard

Getting Used to Docker for Machine Learning Introduction Docker is a powerful addition to any development environment, and this especially rings true for ML Engineers or enthusiasts who want to get started with experimentation without having to go through the hassle of setting up several drivers, packages, and more.

article thumbnail

Meta SAM 2.1 is now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

is a state-of-the-art vision segmentation model designed for high-performance computer vision tasks, enabling advanced object detection and segmentation workflows. You can now use state-of-the-art model architectures, such as language models, computer vision models, and more, without having to build them from scratch.

article thumbnail

Benchmarking Computer Vision Models using PyTorch & Comet

Heartbeat

[link] Transfer learning using pre-trained computer vision models has become essential in modern computer vision applications. In this article, we will explore the process of fine-tuning computer vision models using PyTorch and monitoring the results using Comet. Pre-trained models, such as VGG, ResNet.