AWS Machine Learning Blog

NOVEMBER 6, 2024

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Auto-complete 128

Auto-complete Generative AI Machine Learning Large Language Models 128

Marktechpost

MAY 3, 2024

From completing entire lines of code and functions to writing comments and aiding in debugging and security checks, Copilot serves as an invaluable tool for developers. Trained on a large open-source code dataset, it suggests snippets to full functions, automating repetitive tasks and enhancing code quality.

Artificial Intelligence 115

Artificial Intelligence Artificial Intelligence AI Tools Auto-complete 115

AWS Machine Learning Blog

SEPTEMBER 11, 2023

IaC ensures that customer infrastructure and services are consistent, scalable, and reproducible while following best practices in the area of development operations (DevOps). You can use Lifecycle Configurations to automate customization for your Studio environment. In the navigation bar, in the Region selector, choose US East (N. .

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Auto-complete Machine Learning ML DevOps 132

Marktechpost

DECEMBER 4, 2023

From completing entire lines of code and functions to writing comments and aiding in debugging and security checks, Copilot serves as an invaluable tool for developers. Trained on a large open-source code dataset, it suggests snippets to full functions, automating repetitive tasks and enhancing code quality.

AI Tools 134

AI Tools Auto-complete Artificial Intelligence Artificial Intelligence 134

AWS Machine Learning Blog

JUNE 11, 2024

This feature streamlines the process of launching new instances with the most up-to-date Neuron SDK, enabling you to automate your deployment workflows and make sure you’re always using the latest optimizations. AWS Systems Manager Parameter Store support Neuron 2.18 neuronx-py310-sdk2.18.2-ubuntu20.04 COPY train.py /train.py

Deep Learning 133

Deep Learning ML Automation Auto-complete 133

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.

Deep Learning 134

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Automated retraining mechanism – The training pipeline built with SageMaker Pipelines is triggered whenever a data drift is detected in the inference pipeline. It also provides select access to related services, such as AWS Application Auto Scaling , Amazon S3, Amazon Elastic Container Registry (Amazon ECR), and Amazon CloudWatch Logs.

Data Drift 131

Data Drift Auto-complete ML Automation 131

The MLOps Blog

JUNE 27, 2023

This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. Automated pipelining and workflow orchestration: Platforms should provide tools for automated pipelining and workflow orchestration, enabling you to define and manage complex ML pipelines.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

OCTOBER 18, 2023

Purina used artificial intelligence (AI) and machine learning (ML) to automate animal breed detection at scale. Developing a custom model to analyze images is a significant undertaking that requires time, expertise, and resources, often taking months to complete. Start the model version when training is complete.

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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

IBM Journey to AI blog

MARCH 6, 2024

A McKinsey study claims that software developers can complete coding tasks up to twice as fast with generative AI. DevOps Research and Assessment metrics (DORA), encompassing metrics like deployment frequency, lead time and mean time to recover , serve as yardsticks for evaluating the efficiency of software delivery.

Generative AI 335

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