AWS Machine Learning Blog

NOVEMBER 19, 2024

At the time, I knew little about AI or machine learning (ML). But AWS DeepRacer instantly captured my interest with its promise that even inexperienced developers could get involved in AI and ML. Panic set in as we realized we would be competing on stage in front of thousands of people while knowing little about ML.

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AWS Machine Learning Blog

DECEMBER 9, 2024

With access to a wide range of generative AI foundation models (FM) and the ability to build and train their own machine learning (ML) models in Amazon SageMaker , users want a seamless and secure way to experiment with and select the models that deliver the most value for their business.

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Hacker News

OCTOBER 28, 2024

Since then there have been a lot of other compilers aimed at ML problems, like TVM, MLIR, EON, and GLOW. Image from Wikimedia Even before the first version of TensorFlow was released, the XLA project was integrated as a "domain-specific compiler" for its machine learning graphs.

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Analytics Vidhya

JANUARY 17, 2022

Introduction As a part of writing a blog on the ML or DS topic, I selected a problem statement from Kaggle which is Microsoft malware detection. Here this blog explains how to solve the problem from scratch. In this blog I will explain to […]. This article was published as a part of the Data Science Blogathon.

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ML @ CMU

MARCH 31, 2023

This blog post discusses the effectiveness of black-box model explanations in aiding end users to make decisions. Our work further motivates novel directions for developing and evaluating tools to support human-ML interactions. How can we better support human-ML interactions?

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KDnuggets

AUGUST 16, 2022

This blog outlines a solution to the Kaggle Titanic challenge that employs Privacy-Preserving Machine Learning (PPML) using the Concrete-ML open-source toolkit.

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Analytics Vidhya

FEBRUARY 25, 2022

Introduction As a part of writing a blog on the ML topic, I selected a problem statement is Collaborative Filtering. This is a part of the recommendation systems, we have two techniques, In this bog we major focus on Collaborative-based filtering, this blog is […].

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databricks

MARCH 21, 2023

This blog is authored by Mohamed Afifi Ibrahim, Principal Machine Learning Engineer at Barracuda Networks. 74% of organizations globally have fallen victim to.

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Analytics Vidhya

FEBRUARY 9, 2023

Leveraging ML pipelines can save them time, money, and effort and ensure that their models make accurate predictions and insights. This blog will look at the value ML pipelines bring to data science projects and discuss why they should be adopted.

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AWS Machine Learning Blog

DECEMBER 12, 2024

The new SDK is designed with a tiered user experience in mind, where the new lower-level SDK ( SageMaker Core ) provides access to full breadth of SageMaker features and configurations, allowing for greater flexibility and control for ML engineers. In the following example, we show how to fine-tune the latest Meta Llama 3.1

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Data Science Dojo

JULY 5, 2024

Modern businesses are embracing machine learning (ML) models to gain a competitive edge. Deploying ML models in their day-to-day processes allows businesses to adopt and integrate AI-powered solutions into their businesses. This reiterates the increasing role of AI in modern businesses and consequently the need for ML models.

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KDnuggets

DECEMBER 14, 2022

This blog post uses the Concrete-ML library, allowing data scientists to use machine learning models in fully homomorphic encryption (FHE) settings without any prior knowledge of cryptography. We provide a practical tutorial on how to use the library to build a sentiment analysis model on encrypted data.

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KDnuggets

SEPTEMBER 23, 2024

If you’ve been keeping up, I have been creating a series of free courses that are actually free, for example, the AI & ML Edition. In this blog, I will dive into free courses with Google, from programming. Type in ‘Free courses that are actually free’ in the search bar to look at the rest.

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databricks

DECEMBER 12, 2023

Introduction Databricks Lakehouse Monitoring allows you to monitor all your data pipelines – from data to features to ML models – without additional too.

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databricks

MARCH 6, 2023

ML Virtual Event Enabling Production ML at Scale With Lakehouse March 14, 9 AM PDT / 4 PM GMT Register Now We are.

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databricks

APRIL 3, 2023

In the United States, roughly 7 out of every 1000 mothers suffer from both pregnancy and delivery complications each year1. Of those mothers.

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AWS Machine Learning Blog

OCTOBER 16, 2024

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. SageMaker Processing provisions cluster resources for you to run city-, country-, or continent-scale geospatial ML workloads.

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Towards AI

DECEMBER 26, 2024

4 Things to Keep in Mind Before Deploying Your ML Models This member-only story is on us. medium.com Regardless of the project, it might be software development or ML Model building. Last Updated on December 27, 2024 by Editorial Team Author(s): Richard Warepam Originally published on Towards AI. Upgrade to access all of Medium.

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Analytics Vidhya

FEBRUARY 20, 2023

As the demand for ML models increases, so makes the demand for user-friendly interfaces to interact with these models. Introduction Machine Learning is a fast-growing field, and its applications have become ubiquitous in our day-to-day lives.

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Dataversity

DECEMBER 3, 2024

There is no doubt that machine learning (ML) is transforming industries across the board, but its effectiveness depends on the data it’s trained on. The ML models traditionally rely on real-world datasets to power the recommendation algorithms, image analysis, chatbots, and other innovative applications that make it so transformative.

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databricks

OCTOBER 19, 2023

Machine learning (ML) is more than just developing models; it's about bringing them to life in real-world, production systems. But transitioning from prototype.

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Flipboard

DECEMBER 1, 2023

The blog covers machine learning courses, bootcamps, books, tools, interview questions, cheat sheets, MLOps platforms, and more to master ML and secure your dream job.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Machine learning (ML) helps organizations to increase revenue, drive business growth, and reduce costs by optimizing core business functions such as supply and demand forecasting, customer churn prediction, credit risk scoring, pricing, predicting late shipments, and many others. Let’s learn about the services we will use to make this happen.

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AWS Machine Learning Blog

OCTOBER 22, 2024

Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. He focuses on architecting and implementing large-scale generative AI and classic ML pipeline solutions.

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AWS Machine Learning Blog

OCTOBER 28, 2024

Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. SageMaker Model Monitor monitors the quality of SageMaker ML models in production. Your client applications invoke this endpoint to get inferences from the model.

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Data Science Dojo

FEBRUARY 13, 2025

In this blog, well explore the top AI conferences in the USA for 2025, breaking down what makes each one unique and why they deserve a spot on your calendar. From an enterprise perspective, this conference will help you learn to optimize business processes, integrate AI into your products, or understand how ML is reshaping industries.

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AWS Machine Learning Blog

DECEMBER 4, 2024

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. Using SageMaker, you can build, train and deploy ML models.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

With the increasing use of large models, requiring a large number of accelerated compute instances, observability plays a critical role in ML operations, empowering you to improve performance, diagnose and fix failures, and optimize resource utilization. Anjali Thatte is a Product Manager at Datadog.

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Towards AI

JANUARY 6, 2025

So, in this blog post, I will share my six secret tips, which I hope will show you that in 2025, there are many different ways to get a job in ML. When he found out that his fix actually improved the performance, he knew he had something to share… Read the full blog for free on Medium.

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Data Science Dojo

DECEMBER 28, 2023

That world is not science fiction—it’s the reality of machine learning (ML). In this blog post, we’ll break down the end-to-end ML process in business, guiding you through each stage with examples and insights that make it easy to grasp. Formatting the data in a way that ML algorithms can understand.

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Towards AI

JANUARY 19, 2025

ML algorithms like gradient descent struggle with this kind of feature because large-scale features often dominate the optimization process. Scaling makes sure that all features are treated equally by ML models, because that way we can enhance the models accuracy and convergence speed. It ultimately leads to skewed results.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

Challenges in deploying advanced ML models in healthcare Rad AI, being an AI-first company, integrates machine learning (ML) models across various functions—from product development to customer success, from novel research to internal applications. Rad AI’s ML organization tackles this challenge on two fronts.

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Data Science Dojo

SEPTEMBER 23, 2024

In this blog, we will explore the concept of a confusion matrix using a spam email example. Also learn about the Random Forest Algorithm and its uses in ML Scenario: Email Spam Classification Suppose you have built a machine learning model to classify emails as either “Spam” or “Not Spam.”

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Flipboard

FEBRUARY 11, 2025

This solution ingests and processes data from hundreds of thousands of support tickets, escalation notices, public AWS documentation, re:Post articles, and AWS blog posts. By using Amazon Q Business, which simplifies the complexity of developing and managing ML infrastructure and models, the team rapidly deployed their chat solution.

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databricks

APRIL 16, 2024

Introduction In this blog post we dive into inference with DBRX, the open state-of-the-art large language model (LLM) created by Databricks (see Introducing.

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databricks

MAY 1, 2023

At Databricks, we offer maximal flexibility for choosing compute for ETL and ML/AI workloads. Staying true to the theme of flexibility, we announce.

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Data Science Dojo

APRIL 8, 2024

This blog explores the impact of machine unlearning in improving the results of generative AI. During machine unlearning, an ML model discards previously learned information and or patterns from its knowledge base. The concept is fairly new and still under research in an attempt to improve the overall ML training process.

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