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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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()

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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 »

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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.

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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.

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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 »

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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.

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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.,

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The MLOps Blog

JUNE 4, 2024

TL;DR Using CI/CD workflows to run ML experiments ensures their reproducibility, as all the required information has to be contained under version control. The compute resources offered by GitHub Actions directly are not suitable for larger-scale ML workloads. ML experiments are, by nature, full of uncertainty and surprises.

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AWS Machine Learning Blog

NOVEMBER 7, 2023

Today, we are excited to unveil three generative AI demos, licensed under MIT-0 license : Amazon Kendra with foundational LLM – Utilizes the deep search capabilities of Amazon Kendra combined with the expansive knowledge of LLMs. Having the right setup in place is the first step towards a seamless deployment of the demos. Python 3.6

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Mlearning.ai

JUNE 26, 2023

Introduction Deepchecks is a groundbreaking open-source Python package that aims to simplify and enhance the process of implementing automated testing for machine learning (ML) models. In this article, we will explore the various aspects of Deepchecks and how it can revolutionize the way we validate and maintain ML models.

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AWS Machine Learning Blog

AUGUST 30, 2023

Generative AI is powered by machine learning (ML) models—very large models that are pre-trained on vast amounts of data and commonly referred to as foundation models (FMs). Our solution uses the FLAN-T5 XL FM, using Amazon SageMaker JumpStart , which is an ML hub offering algorithms, models, and ML solutions. We use an ml.t3.medium

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AWS Machine Learning Blog

SEPTEMBER 1, 2023

We use Streamlit for the sample demo application UI. For all the supported parameters, refer to Streaming Python configuration. Because it’s part of the common data formats supported for inference , we can use the default deserializer provided by the SageMaker Python SDK to deserialize the JSON lines data.

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phData

JULY 2, 2024

Snowpark, offered by the Snowflake AI Data Cloud , consists of libraries and runtimes that enable secure deployment and processing of non-SQL code, such as Python, Java, and Scala. In this blog, we’ll cover the steps to get started, including: How to set up an existing Snowpark project on your local system using a Python IDE.

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AWS Machine Learning Blog

JULY 26, 2023

You can check out my 15-chapter book “Pretrain Vision and Large Language Models in Python: End-to-end techniques for building and deploying foundation models on AWS,” which released May 31, 2023, with Packt publishing and is available now on Amazon. More of a reader than a video consumer? Want to jump right into the code?

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Heartbeat

JUNE 26, 2023

A guide to performing end-to-end computer vision projects with PyTorch-Lightning, Comet ML and Gradio Image by Freepik Computer vision is the buzzword at the moment. Today, I’ll walk you through how to implement an end-to-end image classification project with Lightning , Comet ML, and Gradio libraries.

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ODSC - Open Data Science

APRIL 7, 2025

Generative AI tools make it easy to build flashy demos. But transforming those demos into reliable, scalable software is another matter entirely. The New Software Development Lifecycle AI-native products demand a new software development lifecycleone that shares DNA with traditional ML workflows but adapts to the unique nature of LLMs.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

The task involved writing Python code to read data, transform it, and then visualize it in an interesting map. Prerequisites There are a few prerequisites to deploy the demo. You need to generate a Python function that meets the following: Read each file using geopandas. The following are a few of the prompts we included.

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