AWS Machine Learning Blog

OCTOBER 2, 2023

The sample use case used for this series is a visual quality inspection solution that can detect defects on metal tags, which you can deploy as part of a manufacturing process. In a production setting, you can decide to automatically notify another system that takes care of removing faulty metal tags from the production line.

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DagsHub

SEPTEMBER 7, 2023

To mitigate these challenges, using Continuous Integration and Continuous Deployment (CI/CD) methodologies for machine learning can be a game-changer. I’ve created a blog on how to Setup SageMaker for Machine Learning CI/CD pipelines that explains in detail everything you’ll need to set up before starting the training process.

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Data Science 101

AUGUST 27, 2023

The database is good old SQL Server and we have a pretty robust CI/CD pipeline that takes care of builds and deployments. So, first thing for someone starting out: go to GitHub and find some projects that use the “good first issue” tag on some of their issues. Read blogs about tech and development. These can be Websites?

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IBM Data Science in Practice

MARCH 8, 2023

Chip Huyen , the author of Designing Machine Learning Systems , delves into the details of feature platforms in her blog post titled “ Self-Serve Feature Platforms: Architectures and APIs ” In the post, she highlights the differences between feature platforms and feature stores.

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AWS Machine Learning Blog

OCTOBER 20, 2023

ML platform shared and governance services – This function enables setting up and operating common services such as CI/CD, AWS Service Catalog for provisioning environments, and a central model registry for model promotion and lineage. Data scientists create and share new features into the central feature store catalog for reuse.

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Data Science Blog

NOVEMBER 8, 2022

Die Cloud Build API und die Identity and Access Management API werden benötigt, um eine CI/CD Pipeline zu implementieren. mkdir Infrastructure cd Infrastructure touch main.tf Der Quellcode ist in GitHub verfügbar: [link] The post Google Cloud Run – Tutorial appeared first on Data Science Blog.

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AWS Machine Learning Blog

OCTOBER 2, 2023

Use case: Inspecting the quality of metal tags As an ML engineer, it’s important to understand the business case you are working on. Imagine a production line of a manufacturer that engraves metal tags to create customized luggage tags. To make this process more efficient, we use ML to detect faulty tags early in the process.

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IBM Journey to AI blog

FEBRUARY 14, 2024

Clarify computer vision AI-powered computer vision enables image segmentation , which has a wide variety of use cases, including aiding diagnosis in medical imaging, automating locomotion for robotics and self-driving cars, identifying objects of interest in satellite images and photo tagging in social media.

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AWS Machine Learning Blog

AUGUST 29, 2023

In this post, we describe how to create an MLOps workflow for batch inference that automates job scheduling, model monitoring, retraining, and registration, as well as error handling and notification by using Amazon SageMaker , Amazon EventBridge , AWS Lambda , Amazon Simple Notification Service (Amazon SNS), HashiCorp Terraform, and GitLab CI/CD.

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IBM Journey to AI blog

NOVEMBER 29, 2023

In this paper, we showcase how to easily deploy a banking application on both IBM Cloud for Financial Services and Satellite , using automated CI/CD/CC pipelines in a common and consistent manner. To achieve the deployment on Satellite the CI/CC pipelines were reused, and a new CD pipeline was created.

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Iguazio

DECEMBER 5, 2023

In this blog post, we bring the top 23 free human-annotated datasets you can use for your model training and evaluation. This means that humans have added information, like labels or tags. This is where human-annotated datasets come into play. What are Human-annotated Datasets?

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AWS Machine Learning Blog

NOVEMBER 29, 2023

When using this functionality outside of SageMaker Studio, you can define the users who can track the run status on the notebook job dashboard by using tags. For more details about tags to include, see View your notebook jobs and download outputs in the Studio UI dashboard.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

The orchestration leads to a continuous integration and continuous deployment (CI/CD) pipeline deploying an AWS Cloud Development Kit (AWS CDK) app consisting of a SageMaker domain for the respective team. These tags also help track associated costs for the domain.

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phData

FEBRUARY 6, 2024

In this blog, we’ll discuss the basics of dbt build , run , and test , when you should use each of the commands, and finish with some tips on how to optimize your pipelines leveraging dbt. To summarize, when utilizing pipelines that run with automation, things like CI/CD or production refreshes, you will likely want to use dbt build.

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DagsHub

AUGUST 22, 2023

In this blog, we’ll see what SageMaker is and what you’ll need to set up before you start creating your pipelines. How to Set up SageMaker for CI/CD The idea behind CI/CD is that when definitive changes are made to one of the project components (code, data, labels, parameters, etc.), What is Amazon SageMaker?

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The MLOps Blog

AUGUST 4, 2023

Finally, we’ll see how to harness the power of the Pants build system to organize your machine learning monorepo into a robust CI/CD build system. In this blog post, we focus on repositories storing machine learning code. This file should be checked with git if you intend to use Pants for your remote CI/CD.

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Iguazio

JANUARY 22, 2024

In this blog post, we show all the elements and practices you need to to take to productize LLMs and generative AI. You can watch the full talk this blog post is based on, which took place at ODSC West 2023, here. If you train a model on blogs that have toxic language or bias language towards different genders you get the same results.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

This enables data scientists to quickly build and iterate on ML models, and empowers ML engineers to run through continuous integration and continuous delivery (CI/CD) ML pipelines faster, decreasing time to production for models. During operationalization, these environment variables should be set by the CI pipeline.

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The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. CI/CD/CT compatibility : how well does it work with CI/CD tools?

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The MLOps Blog

AUGUST 3, 2023

If you ever want to know some interesting stories about techniques and things, you can look up the Stitch Fix Multithreaded blog. Stefan: Thankfully, Stitch Fix had a blog that had a reasonable amount of readership. I paired that with the blog, in which case, you know, I got a couple of hundred stars in a couple of months.

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The MLOps Blog

DECEMBER 7, 2022

Back in the day, the main pain points were: 1 The architecture deployment wasn’t clearly tagged, and there were parts that heavily relied on manual executions. And that’s when what usually happens, happened: We came for the ML models, we stayed for the ETLs. 3 The SQS queues were messy to maintain.

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The MLOps Blog

OCTOBER 3, 2023

For example, Shopify published a blog post about Merlin. They just need to kind of tag things like “Hey, by the way, we’re using these data sources. You would create a template within GCP, which you then could push out to GitHub, which then would trigger the CI/CD, and then also eventually trigger the deployment process.

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The MLOps Blog

MARCH 21, 2023

Continuous integration and deployment (CI/CD) are crucial for effective MLOps and can enable automation. CI/CD lets your engineers add code and data to start automated development, testing, and deployment, depending on how your organization is set up. My Story DevOps Engineers Who they are? Orchestrators.

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AWS Machine Learning Blog

JANUARY 9, 2023

This ensures portability across platforms, immutable infrastructure deployments, and easier change management and CI/CD implementations. All of these security features are provided out of the box in SageMaker, and can save businesses tens of development months of engineering effort over a 3-year period.

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