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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning Blog

NOVEMBER 19, 2024

This year, generative AI and machine learning (ML) will again be in focus, with exciting keynote announcements and a variety of sessions showcasing insights from AWS experts, customer stories, and hands-on experiences with AWS services.

AWS

AWS ML ML AI

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning Blog

NOVEMBER 13, 2024

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.

ML

ML ML AWS Data Preparation

Deploy Gradio Apps on Hugging Face Spaces

PyImageSearch

DECEMBER 30, 2024

Hugging Face Spaces is a platform for deploying and sharing machine learning (ML) applications with the community. It offers an interactive interface, enabling users to explore ML models directly in their browser without the need for local setup. In the figure below, we can see the Spaces demo for the Visual Question Answering task.

Deep Learning

Deep Learning Deep Learning ML ML

Webinars

What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

MORE WEBINARS

Efficiently build and tune custom log anomaly detection models with Amazon SageMaker

AWS Machine Learning Blog

JANUARY 6, 2025

It usually comprises parsing log data into vectors or machine-understandable tokens, which you can then use to train custom machine learning (ML) algorithms for determining anomalies. You can adjust the inputs or hyperparameters for an ML algorithm to obtain a combination that yields the best-performing model. scikit-learn==0.21.3

Python

Python AWS ML ML

Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements

Flipboard

NOVEMBER 30, 2023

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML) models at any scale. For example: input = "How is the demo going?" Models are packaged into containers for robust and scalable deployments.

ML

ML ML AWS Python

Faster distributed graph neural network training with GraphStorm v0.4

AWS Machine Learning Blog

FEBRUARY 11, 2025

GraphStorm is a low-code enterprise graph machine learning (ML) framework that provides ML practitioners a simple way of building, training, and deploying graph ML solutions on industry-scale graph data. billion edges after adding reverse edges.

AWS

AWS Python ML ML

ML Days in Tashkent — Day 3: Demos and Workshops

PyImageSearch

DECEMBER 18, 2023

But again, stick around for a surprise demo at the end. ? This format made for a fast-paced and diverse showcase of ideas and applications in AI and ML. In just 3 minutes, each participant managed to highlight the core of their work, offering insights into the innovative ways in which AI and ML are being applied across various fields.

ML

ML ML Deep Learning Deep Learning

Qwen 2.5 Coder 32B: Is This Best Open Weight Model Better than GPT-4o and Claude 3.5 Sonnet

Towards AI

NOVEMBER 18, 2024

coder:32b The latest series of Code-Specific Qwen models, with significant improvements in code generation, code reasoning, and… ollama.com You can also try out the model on the demo page of Hugging Face: Qwen2.5 Coder Demo – a Hugging Face Space by Qwen Discover amazing ML apps made by the community huggingface.co

Python

Python Machine Learning Machine Learning ML

Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Flipboard

AUGUST 17, 2023

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

ML

ML ML AWS Data Warehouse

Run ML inference on unplanned and spiky traffic using Amazon SageMaker multi-model endpoints

AWS Machine Learning Blog

FEBRUARY 19, 2024

Model server overview A model server is a software component that provides a runtime environment for deploying and serving machine learning (ML) models. The primary purpose of a model server is to allow effortless integration and efficient deployment of ML models into production systems. For MMEs, each model.py The full model.py

ML

ML ML AWS Deep Learning

Eventual (YC W22) Is Hiring a Developer Relations Manager for Daft (SF)

Hacker News

JULY 18, 2024

ABOUT EVENTUAL Eventual is a data platform that helps data scientists and engineers build data applications across ETL, analytics and ML/AI. Eventual and Daft bridge that gap, making ML/AI workloads easy to run alongside traditional tabular workloads. This is more compute than Frontier, the world's largest supercomputer!

ML

ML ML Python ETL

How to Save Trained Model in Python

The MLOps Blog

MAY 10, 2023

When working on real-world machine learning (ML) use cases, finding the best algorithm/model is not the end of your responsibilities. Reusability & reproducibility: Building ML models is time-consuming by nature. Save vs package vs store ML models Although all these terms look similar, they are not the same.

Python

Python ML ML Database

Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning Blog

JANUARY 29, 2025

Watch this video demo for a step-by-step guide. You can customize the retry behavior using the AWS SDK for Python (Boto3) Config object. Once you are ready to import the model, use this step-by-step video demo to help you get started. The restoration time varies depending on the on-demand fleet size and model size.

AWS

AWS ML ML AI

Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

Flipboard

APRIL 24, 2025

The API is linked to an AWS Lambda function, which implements and orchestrates the processing steps described earlier using a programming language of the users choice (such as Python) in a serverless manner. The demo code is available in the GitHub repository. Thomas Matthew is an AL/ML Engineer at Cisco.

SQL

SQL Database AWS ML

Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

AWS Machine Learning Blog

MARCH 19, 2025

Implementation details and demo setup in an AWS account As a prerequisite, we need to make sure that we are working in an AWS Region with Amazon Bedrock support for the foundation model (here, we use Anthropics Claude 3.5 For this demo setup, we describe the manual steps taken in the AWS console.

AWS

AWS AI AI Cloud Computing

Using Generative AI to Build Generative AI

O'Reilly Media

FEBRUARY 25, 2025

In this post I want to talk about using generative AI to extend one of my academic software projectsthe Python Tutor tool for learning programmingwith an AI chat tutor. Python Tutor is mainly used by students to understand and debug their homework assignment code step-by-step by seeing its call stack and data structures.

AI

AI AI Python Computer Science

Building a Multimodal Gradio Chatbot with Llama 3.2 Using the Ollama API

Flipboard

FEBRUARY 10, 2025

Whether youre new to Gradio or looking to expand your machine learning (ML) toolkit, this guide will equip you to create versatile and impactful applications. Gradio is an open-source Python library that enables developers to create user-friendly and interactive web applications effortlessly. and the Ollama API, just keep reading.

Deep Learning

Deep Learning Deep Learning Python AI

Amazon Bedrock Custom Model Import now generally available

AWS Machine Learning Blog

OCTOBER 21, 2024

SageMaker JumpStart provides FMs through two primary interfaces: SageMaker Studio and the SageMaker Python SDK. For this example, we take a sample context and add to demo the concept: input_output_demarkation_key = "nn### Response:n" question = "Tell me what was the improved inflow value of cash?" degree in Electrical Engineering.

AWS

AWS AI AI ML

How Sportradar used the Deep Java Library to build production-scale ML platforms for increased performance and efficiency

AWS Machine Learning Blog

APRIL 19, 2023

Right now, most deep learning frameworks are built for Python, but this neglects the large number of Java developers and developers who have existing Java code bases they want to integrate the increasingly powerful capabilities of deep learning into. Business requirements We are the US squad of the Sportradar AI department.

ML

ML ML Deep Learning Deep Learning

An integrated experience for all your data and AI with Amazon SageMaker Unified Studio (preview)

Flipboard

DECEMBER 11, 2024

Second, because data, code, and other development artifacts like machine learning (ML) models are stored within different services, it can be cumbersome for users to understand how they interact with each other and make changes. Under Quick setup settings , for Name , enter a name (for example, demo). Choose Continue.

SQL

SQL AWS Data Lakes AI

Snowflake Snowpark: cloud SQL and Python ML pipelines

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL

SQL ML ML Python

Snowflake Snowpark: cloud SQL and Python ML pipelines

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL

SQL ML ML Python

Build Streamlit apps in Amazon SageMaker Studio

AWS Machine Learning Blog

APRIL 11, 2023

Developing web interfaces to interact with a machine learning (ML) model is a tedious task. With Streamlit , developing demo applications for your ML solution is easy. Streamlit is an open-source Python library that makes it easy to create and share web apps for ML and data science. sh setup.sh is modified on disk.

ML

ML ML AWS Data Scientist

Speed up Your ML Projects With Spark

Towards AI

JUNE 25, 2024

As a Python user, I find the {pySpark} library super handy for leveraging Spark’s capacity to speed up data processing in machine learning projects. We will use this table to demo and test our custom functions. Image generated by Gemini Spark is an open-source distributed computing framework for high-speed data processing. distinct().count()

ML

ML ML EDA Data Wrangling

Code Llama code generation models from Meta are now available via Amazon SageMaker JumpStart

AWS Machine Learning Blog

OCTOBER 2, 2023

You can try out this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. What is SageMaker JumpStart With SageMaker JumpStart, ML practitioners can choose from a growing list of best-performing foundation models.

Python

Python ML ML Machine Learning

6 AI tools revolutionizing data analysis: Unleashing the best in business

Data Science Dojo

JULY 17, 2023

It is similar to TensorFlow, but it is designed to be more Pythonic. Scikit-learn Scikit-learn is an open-source machine learning library for Python. Explore the top 10 machine learning demos and discover cutting-edge techniques that will take your skills to the next level. It is open-source, so it is free to use and modify.

Data Analysis

Data Analysis Data Analysis Tableau Machine Learning

Top AI/ML Announcements from Snowday 2023

phData

NOVEMBER 2, 2023

From cutting-edge innovations in MLOps to powerful integrations with Large Language Models (LLMs), Snowflake’s event was chock full of exciting announcements for Data Scientists and ML Engineers. In this post, we’ll recap some of the announcements that we’re most excited about in the AI/ML space.

ML

ML ML SQL Data Scientist

Accelerate custom labeling workflows in Amazon SageMaker Ground Truth without using AWS Lambda

AWS Machine Learning Blog

OCTOBER 31, 2024

The following example demonstrates how to do this using Python and Boto3. He focuses on building and maintaining scalable AI/ML products, like Amazon SageMaker Ground Truth and Amazon Bedrock Model Evaluation. In his free time, Sundar loves exploring new places, sampling local eateries and embracing the great outdoors.

AWS

AWS Natural Language Processing ML ML

From Jupyter to Production: Why Deployment Matters in LLM Projects

ODSC - Open Data Science

MAY 20, 2025

If youre a Python user looking to move fast from prototype to shareable app, Streamlit is your bestfriend. With just a few lines of Python, you can create an interactive web UItext boxes, buttons, display panelsand plug it directly into your LLM logic. These tools help you move beyond cool demo to maintainable service.

Data Science

Data Science Python AI AI

ML Days in Tashkent — Day 1: City Tour

PyImageSearch

DECEMBER 4, 2023

Home Table of Contents ML Days in Tashkent — Day 1: City Tour Arriving at Tashkent! But stick around for a surprise demo at the end. pip install -q keras-nightly On Lines 1-5 , we start by installing the necessary Python packages. os is a standard Python library, with os being used to set environment variables.

ML

ML ML Machine Learning Machine Learning

Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly Media

MARCH 25, 2025

Someone hacks together a quick demo with ChatGPT and LlamaIndex. The system is inconsistent, slow, hallucinatingand that amazing demo starts collecting digital dust. Check out the graph belowsee how excitement for traditional software builds steadily while GenAI starts with a flashy demo and then hits a wall of challenges?

AI

AI AI ML ML

Use GitHub Actions with Azure ML Studio: train, deploy/publish, monitor

Mlearning.ai

AUGUST 28, 2023

One aspect of this Data Science exam experience that I thought was lacking, was doing a complete MLOps workflow using GitHub Actions in addition to the Python SDK. yml script to configure a virtual machine to run the training script on, [2] running the scripts using GitHub Actions instead of with the azureml python SDK.

Azure

Azure ML ML Data Science

Build AI Better with These ODSC East 2023 Demo Talks

ODSC - Open Data Science

APRIL 20, 2023

Much can be accomplished at the ODSC East AI Expo and Demo Hall , from connecting with partner representatives to getting caught up on the latest developments in AI applications. Topics covered will range from ML-based recommendations to user-friendly interfaces. Check out some of our confirmed sessions below coming this May 9th-11th.

Data Science

Data Science Azure AI AI

8 ODSC Europe Training Sessions to Boost Your Data Science Career

ODSC - Open Data Science

MAY 22, 2023

Training AI-Powered Algorithmic Trading with Python Dr. Yves J. Hilpisch | The AI Quant | CEO The Python Quants & The AI Machine, Adjunct Professor of Computational Finance This session will cover the essential Python topics and skills that will enable you to apply AI and Machine Learning (ML) to Algorithmic Trading.

Data Science

Data Science Machine Learning Machine Learning Python

Explore advanced techniques for hyperparameter optimization with Amazon SageMaker Automatic Model Tuning

AWS Machine Learning Blog

NOVEMBER 10, 2023

Creating high-performance machine learning (ML) solutions relies on exploring and optimizing training parameters, also known as hyperparameters. It provides key functionality that allows you to focus on the ML problem at hand while automatically keeping track of the trials and results. We use a Random Forest from SkLearn.

ML

ML ML Algorithm Python

Meet Quivr: An Open-Source Project Designed to Store and Retrieve Unstructured Information like a Second Brain

Flipboard

JULY 24, 2023

It has an official website from which you can access the premium version of Quivr by clicking on the button ‘Try demo.’ You should also have the official, and the latest version of Python preinstalled on your device. Text and multimedia are two common types of unstructured content.

Natural Language Processing

Natural Language Processing Artificial Intelligence Artificial Intelligence Data Science

MCP: What It Is and Why It Matters—Part 1

Flipboard

MAY 8, 2025

Heres a demo of me creating a low-poly dragon guarding treasure scene in just a few sentences Video: Siddharth Ahuja 2. Developers had to wire up each tool separately, often using different methods: One tool might require the AI to output JSON; another needed a custom Python wrapper; another a special prompt format.

Database

Database AI AI SQL

Share medical image research on Amazon SageMaker Studio Lab for free

Flipboard

FEBRUARY 7, 2023

Amazon SageMaker Studio Lab provides no-cost access to a machine learning (ML) development environment to everyone with an email address. Make sure to choose the medical-image-ai Python kernel when running the TCIA notebooks in Studio Lab. Open-source libraries like MONAI Core and itkWidgets also run on Amazon SageMaker Studio.

AWS

AWS ML ML Deep Learning

Collaborate Smarter, Not Harder: Comet’s Integrations for Effective ML Project Management

Heartbeat

JUNE 5, 2023

Without proper tracking, optimization, and collaboration tools, ML practitioners can quickly become overwhelmed and lose track of their progress. Comet’s integrations are modular and customizable, enabling teams to incorporate new approaches and tools to their ML platforms. This is where Comet comes in.

ML

ML ML Machine Learning Machine Learning

The Lazy Predict Package in Python to Easily Build Machine Learning Models

Mlearning.ai

MARCH 19, 2023

This article will provide a demo of the LazyPredict package in Python. The demo will walkthrough how easily this package can be used for a… Continue reading on MLearning.ai »

Python

Python Machine Learning Machine Learning ML

Building AI with AutoML and Composable ML

DataRobot

JUNE 23, 2021

To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. Composable ML is currently available through a private beta program, and I want to share what we see successful users doing. Composable ML then lets you add new types of feature engineering or build entirely new models.

ML

ML ML Data Scientist Machine Learning

Introduction to PyGWalker Package (the Tableau UI in Python)

Mlearning.ai

MARCH 5, 2023

In this article we will walk through a demo of the PyGWalker package in Python. For this we will use NBA stats from the below web page: Continue reading on MLearning.ai »

Python

Python Tableau Data Visualization ML

Deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK

AWS Machine Learning Blog

MAY 23, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of virtually infinite compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are rapidly adopting and using ML technologies to transform their businesses.

AWS

AWS AI AI ML

MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. 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.,

Machine Learning

Machine Learning Machine Learning ML ML

Your guide to generative AI and ML at AWS re:Invent 2024

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

Webinars

Trending Sources

Deploy Gradio Apps on Hugging Face Spaces

Webinars

Efficiently build and tune custom log anomaly detection models with Amazon SageMaker

Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements

Faster distributed graph neural network training with GraphStorm v0.4

ML Days in Tashkent — Day 3: Demos and Workshops

Qwen 2.5 Coder 32B: Is This Best Open Weight Model Better than GPT-4o and Claude 3.5 Sonnet

Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Run ML inference on unplanned and spiky traffic using Amazon SageMaker multi-model endpoints

Eventual (YC W22) Is Hiring a Developer Relations Manager for Daft (SF)

How to Save Trained Model in Python

Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

Using Generative AI to Build Generative AI

Building a Multimodal Gradio Chatbot with Llama 3.2 Using the Ollama API

Amazon Bedrock Custom Model Import now generally available

How Sportradar used the Deep Java Library to build production-scale ML platforms for increased performance and efficiency

An integrated experience for all your data and AI with Amazon SageMaker Unified Studio (preview)

Snowflake Snowpark: cloud SQL and Python ML pipelines

Snowflake Snowpark: cloud SQL and Python ML pipelines

Build Streamlit apps in Amazon SageMaker Studio

Speed up Your ML Projects With Spark

Code Llama code generation models from Meta are now available via Amazon SageMaker JumpStart

6 AI tools revolutionizing data analysis: Unleashing the best in business

Top AI/ML Announcements from Snowday 2023

Accelerate custom labeling workflows in Amazon SageMaker Ground Truth without using AWS Lambda

From Jupyter to Production: Why Deployment Matters in LLM Projects

ML Days in Tashkent — Day 1: City Tour

Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

Use GitHub Actions with Azure ML Studio: train, deploy/publish, monitor

Build AI Better with These ODSC East 2023 Demo Talks

8 ODSC Europe Training Sessions to Boost Your Data Science Career

Explore advanced techniques for hyperparameter optimization with Amazon SageMaker Automatic Model Tuning

Meet Quivr: An Open-Source Project Designed to Store and Retrieve Unstructured Information like a Second Brain

MCP: What It Is and Why It Matters—Part 1

Share medical image research on Amazon SageMaker Studio Lab for free

Collaborate Smarter, Not Harder: Comet’s Integrations for Effective ML Project Management

The Lazy Predict Package in Python to Easily Build Machine Learning Models

Building AI with AutoML and Composable ML

Introduction to PyGWalker Package (the Tableau UI in Python)

Deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK

MLOps Landscape in 2023: Top Tools and Platforms

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