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Building a Business with a Real-Time Analytics Stack, Streaming ML Without a Data Lake, and…

ODSC - Open Data Science

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.

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Streaming Machine Learning Without a Data Lake

ODSC - Open Data Science

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

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Watch the Top ODSC Europe 2023 Virtual Sessions Here

ODSC - Open Data Science

Time Series Forecasting for Managers — All Forecasts Are Wrong but Some Are Useful Tanvir Ahmed Shaikh | Data Strategist (Director) | Genentech, Inc Time series forecasting remains an under-appreciated technique in data science education, often overshadowed by more popular machine learning methods.

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All of the Free Virtual Sessions Coming to ODSC Europe 2023

ODSC - Open Data Science

Wednesday, June 14th Me, my health, and AI: applications in medical diagnostics and prognostics: Sara Khalid | Associate Professor, Senior Research Fellow, Biomedical Data Science and Health Informatics | University of Oxford Iterated and Exponentially Weighted Moving Principal Component Analysis : Dr. Paul A.

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Pictures and Highlights from ODSC Europe 2023

ODSC - Open Data Science

Some of our most popular in-person sessions were: Data Communication in the Age of AI: Alan Rutter | Founder | Fire Plus Algebra Autoencoders — a Magical Approach to Unsupervised Machine Learning: Oliver Zeigermann | Blue Collar ML Architect | Freelancer Fast Option Pricing Using Deep Learning Methods: Chakri Cherukuri | Senior Quantitative Researcher (..)

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Bundesliga Match Fact Keeper Efficiency: Comparing keepers’ performances objectively using machine learning on AWS

AWS Machine Learning Blog

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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Comparing Tools For Data Processing Pipelines

The MLOps Blog

Data pipeline stages But before delving deeper into the technical aspects of these tools, let’s quickly understand the core components of a data pipeline succinctly captured in the image below: Data pipeline stages | Source: Author What does a good data pipeline look like?