Remove about staff-directory
article thumbnail

Would Your Company Pass a Cybersecurity Polygraph Test?

Unite.AI

This encompasses elements like secure servers, advanced firewalls, efficient intrusion detection mechanisms, and Active Directory security safeguards. This encompasses your data safety guidelines, breach response blueprint, and staff training modules. Make sure they are relevant and in sync with modern best practices.

article thumbnail

Build an end-to-end MLOps pipeline using Amazon SageMaker Pipelines, GitHub, and GitHub Actions

AWS Machine Learning Blog

Data scientists, ML engineers, IT staff, and DevOps teams must work together to operationalize models from research to deployment and maintenance. Copy the contents of the seed code directory into the root of your GitHub repository. For instance, the.github directory should be under the root of your GitHub repository.

ML 100
professionals

Sign Up for our Newsletter

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

article thumbnail

How to detect and patch a Log4J vulnerability 

IBM Journey to AI blog

Log4Shell is a result of how vulnerable versions of Log4j handle the Java Naming and Directory Interface (JNDI), an API that Java apps use to access resources hosted on external servers. On Linux, Microsoft Windows, and macOS operating systems, security teams can search file directories for instances of Log4j using the command line interface.

IDP 209
article thumbnail

How to extend the functionality of AWS Trainium with custom operators

AWS Machine Learning Blog

Conclusion Modern state-of-the-art model architectures require an increasing number of resources from engineering staff (data scientists, ML engineers, MLOps engineers, and others) to actual infrastructure including storage, compute, memory, and accelerators. header from the torchneuron library: #include "torchneuron/register.h"

article thumbnail

Amazon SageMaker built-in LightGBM now offers distributed training using Dask

AWS Machine Learning Blog

The cat_index.json file should be put under the training data directory, as shown in the following example. About the authors Dr. Xin Huang is an Applied Scientist for Amazon SageMaker JumpStart and Amazon SageMaker built-in algorithms. Will is passionate about using technology in innovative ways to positively impact the community.

article thumbnail

Fine-tune and deploy Llama 2 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium

AWS Machine Learning Blog

For more information about version updates, refer to Shut down and Update Studio Classic Apps. Deploy the Llama-2-13b model with SageMaker Jumpstart You can choose the model card to view details about the model such as license, data used to train, and how to use it. The number of files under the train directory should equal to 1.