AWS Machine Learning Blog

MAY 16, 2024

When training is complete (through the Lambda step), the deployed model is updated to the SageMaker endpoint. When the preprocessing batch was complete, the training/test data needed for training was partitioned based on runtime and stored in Amazon S3. This means keeping the same PyTorch and Python versions for training and inference.

Deep Learning 130

Deep Learning Auto-complete Algorithm ML 130

AWS Machine Learning Blog

NOVEMBER 9, 2023

Create a KMS key in the dev account and give access to the prod account Complete the following steps to create a KMS key in the dev account: On the AWS KMS console, choose Customer managed keys in the navigation pane. Choose Create key. For Key type , select Symmetric. For Script Path , enter Jenkinsfile. Choose Save.

Data Drift 130

Data Drift Auto-complete ML Automation 130

The MLOps Blog

JUNE 27, 2023

For example, if your team is proficient in Python and R, you may want an MLOps tool that supports open data formats like Parquet, JSON, CSV, etc., Can you see the complete model lineage with data/models/experiments used downstream? Auto-annotation tools such as Meta’s Segment Anything Model and other AI-assisted labeling techniques.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

OCTOBER 18, 2023

This post details how Purina used Amazon Rekognition Custom Labels , AWS Step Functions , and other AWS Services to create an ML model that detects the pet breed from an uploaded image and then uses the prediction to auto-populate the pet attributes. Start the model version when training is complete.

Auto-complete 130

Auto-complete Auto-classification Machine Learning Automation 130

AWS Machine Learning Blog

JULY 16, 2024

It manages the availability and scalability of the Kubernetes control plane, and it provides compute node auto scaling and lifecycle management support to help you run highly available container applications. Training Now that our data preparation is complete, we’re ready to train our model with the created dataset.

Generative AI 133

Generative AI Auto-complete Auto-classification AI 133

AWS Machine Learning Blog

JUNE 29, 2023

image and Python 3 kernel from SageMaker Studio so that we have a recent Python 3.10 Clean up Complete the following steps to clean up your resources: Shut down the SageMaker Studio instances to avoid incurring additional costs. She has a decade of experience in DevOps, infrastructure, and ML. bitsandbytes==0.39.1 %pip

Auto-complete 144

Auto-complete Large Language Models Machine Learning ML 144

Mlearning.ai

MAY 3, 2023

An open-source, low-code Python wrapper for easy usage of the Large Language Models such as ChatGPT, AutoGPT, LLaMa, GPT-J, and GPT4All An introduction to “ pychatgpt_gui” —  A GUI-based APP for LLM’s with custom-data training and pre-trained inferences. It is an open-source python package. The launched APP snapshot is as seen below.

Large Language Models 52

Large Language Models Python Auto-complete Natural Language Processing 52

AWS Machine Learning Blog

NOVEMBER 6, 2024

The code artifacts are in Python. time.sleep(10) The transcription job will take a few minutes to complete. When the job is complete, you can inspect the transcription output and check the plain text transcript that was generated (the following has been trimmed for brevity): # Get the Transcribe Output JSON file s3 = boto3.client('s3')

Auto-complete 123

Auto-complete Generative AI Machine Learning Large Language Models 123