AWS Machine Learning Blog

SEPTEMBER 11, 2024

In this post, we demonstrate how to build a robust real-time anomaly detection solution for streaming time series data using Amazon Managed Service for Apache Flink and other AWS managed services. This solution employs machine learning (ML) for anomaly detection, and doesn’t require users to have prior AI expertise.

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AWS Machine Learning Blog

JANUARY 6, 2023

The key requirement for TR’s new machine learning (ML)-based personalization engine was centered around an accurate recommendation system that takes into account recent customer trends. ML training pipeline. TR customer data is changing at a faster rate than the business rules can evolve to reflect changing customer needs.

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Precisely

DECEMBER 28, 2023

More than ever, advanced analytics, ML, and AI are providing the foundation for innovation, efficiency, and profitability. Streaming data pipelines, by extension, offer an architecture capable of handling large volumes of data, accommodating millions of events in near real time. The concept of streaming data was born of necessity.

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AWS Machine Learning Blog

NOVEMBER 3, 2023

This process comprises two key components: event data and optical tracking data. Event data collection entails gathering the fundamental building blocks of the game. For the precision needed in shot speed calculations, we must ensure that the ball’s position aligns precisely with the moment of the event.

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ODSC - Open Data Science

JULY 22, 2023

Expo Hall ODSC events are more than just data science training and networking events. Thank you to everyone who attended for making this event possible, and showing once again why we do what we do — connecting the greater data science community together to push the industry forward. What’s next?

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ODSC - Open Data Science

JULY 14, 2023

Probabilistic Machine Learning for Finance and Investing Deepak Kanungo | Founder and CEO, Advisory Board Member | Hedged Capital LLC, AIKON This session will introduce you to the reasons why probabilistic machine learning is the next generation of AI in finance and investing.

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The MLOps Blog

FEBRUARY 5, 2023

Streaming data is a continuous flow of information and a foundation of event-driven architecture software model” – RedHat Enterprises around the world are becoming dependent on data more than ever. A streaming data pipeline is an enhanced version which is able to handle millions of events in real-time at scale.

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DagsHub

APRIL 7, 2024

These pipelines cover the entire lifecycle of an ML project, from data ingestion and preprocessing, to model training, evaluation, and deployment. Adopted from [link] In this article, we will first briefly explain what ML workflows and pipelines are. around the world to streamline their data and ML pipelines.

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DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. This article will discuss managing unstructured data for AI and ML projects. You will learn the following: Why unstructured data management is necessary for AI and ML projects. How to properly manage unstructured data.

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Mlearning.ai

MAY 16, 2023

In data engineering, the Pub/Sub pattern can be used for various use cases such as real-time data processing, event-driven architectures, and data synchronization across multiple systems. The company can use the Pub/Sub pattern to process customer events such as product views, add to cart, and checkout.

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The MLOps Blog

MARCH 15, 2023

A typical data pipeline involves the following steps or processes through which the data passes before being consumed by a downstream process, such as an ML model training process. Data Ingestion : Involves raw data collection from origin and storage using architectures such as batch, streaming or event-driven.

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DagsHub

JANUARY 14, 2025

A massive amount of diverse data powers today's ML models. Similar Audio: Audio recordings of the same event or sound but with different microphone placements or background noise. Tools like Apache Kafka and Apache Flink can be configured for this purpose.

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The MLOps Blog

AUGUST 11, 2023

There comes a time when every ML practitioner realizes that training a model in Jupyter Notebook is just one small part of the entire project. At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. What are ML pipeline architecture design patterns?

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AWS Machine Learning Blog

MARCH 30, 2023

The result is a machine learning (ML)-powered insight that allows fans to easily evaluate and compare the goalkeepers’ proficiencies. An ML model is trained through Amazon SageMaker , using data from four seasons of the first and second Bundesliga, encompassing all shots that landed on target (either resulting in a goal or being saved).

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ODSC - Open Data Science

MAY 24, 2023

Building a Business with a Real-Time Analytics Stack, Streaming ML Without a Data Lake, and Google’s PaLM 2 Building a Pizza Delivery Service with a Real-Time Analytics Stack The best businesses react quickly and with informed decisions. Here’s a use case of how you can use a real-time analytics stack to build a pizza delivery service.

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phData

SEPTEMBER 27, 2024

In this guide, we will explore concepts like transitional modeling for customer profiles, the power of event logs for customer behavior, persistent staging for raw customer data, real-time customer data capture, and much more. Rich Context: Each event carries with it a wealth of contextual information. What is Activity Schema Modeling?

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