AWS Machine Learning Blog

JANUARY 9, 2024

Large language models (LLMs) are a type of FM that generate text as a response of the user inference. The following table outlines the specifications for this deployment. In the configuration, you define the number of GPUs used per replica of a model as 4 for SM_NUM_GPUS. You then define the instructions as per the use case.

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AWS Machine Learning Blog

MARCH 15, 2024

This traditional approach poses several challenges: it heavily depends on manual processes, struggles to efficiently scale with increasing customer demands, introduces the potential for human errors, and operates within specific hours of availability. Choose Create table. For Table name , enter a name (for example, ItemDetails ).

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Heartbeat

JANUARY 5, 2024

Callbacks : Introduce examination and introspection as an additional layer of support. Python : Great for including AI in Python-based software or data pipelines. Query : A user input to the system by a human user. LangChain is provided in two programming languages: Python and JavaScript.

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AWS Machine Learning Blog

APRIL 24, 2024

Conversational artificial intelligence (AI) assistants are engineered to provide precise, real-time responses through intelligent routing of queries to the most suitable AI functions. With AWS generative AI services like Amazon Bedrock , developers can create systems that expertly manage and respond to user requests. on Amazon Bedrock.

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AWS Machine Learning Blog

APRIL 16, 2024

Finally, to enable a broader audience of users to generate SQL queries from natural language input in their notebooks, we show you how to deploy these Text-to-SQL models using Amazon SageMaker endpoints. This new feature enables you to perform various functions. If your notebook environments are running on SageMaker Distribution 1.6

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AWS Machine Learning Blog

DECEMBER 6, 2023

Conversational AI has come a long way in recent years thanks to the rapid developments in generative AI, especially the performance improvements of large language models (LLMs) introduced by training techniques such as instruction fine-tuning and reinforcement learning from human feedback.

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phData

DECEMBER 22, 2023

In this festive blog, we’re going to explore how Santa could plan the most optimal flight path for his famous route on Christmas Eve by building a data application built on the Snowflake Data Cloud. The purpose of this step is to introduce randomness and help the population escape from local minima. Snowflake Setup 1.

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AWS Machine Learning Blog

MARCH 13, 2024

Explore the Gemma model in Jumpstart You can access Gemma foundation models through SageMaker JumpStart in the SageMaker Studio UI and the SageMaker Python SDK. Deploy Gemma with SageMaker Python SDK You can find the code showing the deployment of Gemma on JumpStart and an example of how to use the deployed model in this GitHub notebook.

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The MLOps Blog

JANUARY 26, 2024

In this article, I’ll introduce you to a unified architecture for ML systems built around the idea of FTI pipelines and a feature store as the central component. Each of these tasks can be performed by a pipeline: A program that runs on some schedule with well-defined inputs and outputs. This can seem daunting.

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AWS Machine Learning Blog

APRIL 20, 2023

The following table summarizes the details of our use case. Additionally, you can define the end-to-end model latency to predict if a transaction is fraudulent and define the maximum concurrent transactions to the model for prediction. You can now run default and advanced jobs using a single function: right_size.

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Flipboard

MARCH 27, 2023

Table of Contents What’s New in PyTorch 2.0? The success of PyTorch is attributed to its simplicity, first-class Python integration, and imperative style of programming. This blog series aims to understand and test the capabilities of PyTorch 2.0 is available as a Python pip package. What’s New in PyTorch 2.0?

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AWS Machine Learning Blog

APRIL 17, 2023

The custom transform feature supports Python, PySpark, and SQL as different steps in code snippets. NLTK is a leading platform for building Python programs to work with human language data. You can create a custom transform using Pandas, PySpark, Python user-defined functions, and SQL PySpark.

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PyImageSearch

FEBRUARY 27, 2023

Table of Contents Learning JAX in 2023: Part 2 — JAX’s Power Tools grad , jit , vmap , and pmap ?? Important Functional Transformations Pure Functions jaxpr jax.grad jax.jit jax.vmap jax.pmap ? In the previous tutorial , we were introduced to JAX, and its predecessors autograd and xla.

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phData

DECEMBER 4, 2023

This blog was originally written by Erik Hyrkas and updated for 2024 by Justin Delisi This isn’t meant to be a technical how-to guide — most of those details are readily available via a quick Google search — but rather an opinionated review of key processes and potential approaches. Want to save this guide for later?

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PyImageSearch

FEBRUARY 19, 2024

Home Table of Contents Image Classification with Gemini Pro Introduction to Gemini Pro for Image Classification Transitioning from Image Processing to Image Classification with Gemini Pro Comparative Analysis: Gemini Pro vs. ChatGPT-3.5 We introduced Gemini Pro, analyzed the Python code it generated, and compared it with ChatGPT-3.5

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Research shows that not only do risks for bias and toxicity transfer from pre-trained foundation models (FM) to task-specific generative AI services, but that tuning an FM for specific tasks, on incremental datasets, introduces new and possibly greater risks. The core evaluation function, evaluate() , is extensible. What is FMEval?

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AWS Machine Learning Blog

OCTOBER 24, 2023

Generative AI not only introduces enhanced capabilities in document processing, it also introduces a dynamic adaptability to changing data patterns. The benefit of defining a deterministic schema is also to achieve key normalization so that we have a known set of keys to process in our postprocessing logic.

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AWS Machine Learning Blog

NOVEMBER 20, 2023

Introducing the KT project and defining the problem The AI Food Tag model pre-trained by KT is based on the vision transformers (ViT) architecture and has more model parameters than their previous vision model to improve accuracy. It helps users understand which operations are consuming resources. region_name}.amazonaws.com/pytorch-training:2.0.0-gpu-py310-cu118-ubuntu20.04-sagemaker'

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The MLOps Blog

AUGUST 3, 2023

What we’re targeting first is helping you replace that procedural Python code with Hamilton code that you describe, which I can go into detail a little bit more. You could almost think of Hamilton as DBT for Python functions. It gives a very opinionary way of writing Python. Piotr: This is procedural Python code.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Design principles The reliability pillar encompasses the ability of an IDP solution to perform document processing correctly and consistently when it’s expected and according to the defined business rules. This removes the potential for introducing human error and enables you to test before changing to your production environment.

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AWS Machine Learning Blog

JUNE 28, 2023

The inputs are “A boxer dancing on a table,” “A lady on the beach in swimming wear, water color style,” and “A dog in a suit.” The steps in the workflow are as follows: The user send a prompt to generate an image. Although generative AI solutions are powerful and useful, they can also be vulnerable to manipulation and abuse.

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The MLOps Blog

AUGUST 4, 2023

or as narrow as a couple of Python projects developed by a small team thrown into a single repository. In this blog post, we focus on repositories storing machine learning code. Let’s just put the basics on the table. How to set up ML monorepo with Python?

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AWS Machine Learning Blog

AUGUST 29, 2023

GitLab CI/CD serves as the macro-orchestrator, orchestrating model build and model deploy pipelines, which include sourcing, building, and provisioning Amazon SageMaker Pipelines and supporting resources using the SageMaker Python SDK and Terraform.

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The MLOps Blog

MAY 31, 2023

We can collect and use user-product historical interaction data to train recommendation system algorithms. Traditional Collaborative Filtering or Neural Collaborative Filter algorithms that rely on users’ past engagement with products are widely used to solve such Personalisation and Recommendation problems.

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Chatbots Life

MAY 12, 2023

Table of contents: · What is ChatGPT? · Unfortunately, the model’s release wasn’t accompanied by a research paper, and its only official description can be found on the OpenAI blog. We can ask the model to generate a python function or a recipe for a cheesecake. We will answer the question “ Will you lose your job?”

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AWS Machine Learning Blog

JUNE 13, 2023

The objective was to transfer this functionality to the model itself to clarify the separation of responsibilities, modularize and simplify their code, and reduce the load on the API. Ensemble models allow for defining and ordering steps in the inference logic, with each step represented by a Triton model of any backend type.

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AWS Machine Learning Blog

MARCH 6, 2023

Within one launch command, Amazon SageMaker launches a fully functional, ephemeral compute cluster running the task of your choice, and with enhanced ML features such as metastore, managed I/O, and distribution. The AWS Python SDK Boto3 may also be combined with Torch Dataset classes to create custom data loading code.

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AWS Machine Learning Blog

JULY 31, 2023

We first discuss the solution at the high level and its user experience. Genetic databases – A genetic database is one or more sets of genetic data stored together with software to enable users to retrieve genetic data. Next, we walk you through how to easily set up compute-optimized workflows of AlphaFold2 and OpenFold with SageMaker.

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PyImageSearch

JULY 24, 2023

Home Table of Contents What Is Keras Core? This lesson introduces Keras Core and its multi-backend functionalities. Keras is a user-friendly tool written in Python for Deep Learning. Boosting User Experience: PyTorch users, rejoice! To learn how to navigate the Keras Core library, just keep reading.

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Alation

FEBRUARY 17, 2023

In this blog, I’ll address some of the questions we did not have time to answer live, pulling from both Dr. Reichental’s book as well as my own experience as a data governance leader for 30+ years. When building out policies, the first thing to do is define how you are going to collect data, and specify ownership.

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The MLOps Blog

MARCH 21, 2023

How to understand your users (data scientists, ML engineers, etc.). Gathering requirements from your users. We ask this during product demos, user and support calls, and on our MLOps LIVE podcast. The principles of MLOps can actively help you frame how you define the goals of your machine learning platform.

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