article thumbnail

Machine learning model serving architectures

Xebia

After months of crunching data, plotting distributions, and testing out various machine learning algorithms you have finally proven to your stakeholders that your model can deliver business value. Selecting the right architectural serving pattern is paramount in creating the most business value from your model.

article thumbnail

Real-time Data, Machine Learning, and Results: The Evidence Mounts

CIO

From delightful consumer experiences to attacking fuel costs and carbon emissions in the global supply chain, real-time data and machine learning (ML) work together to power apps that change industries. Data architecture coherence. more machine learning use casesacross the company.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Enhancing customer care through deep machine learning at Travelers

CIO

And we recognized as a company that we needed to start thinking about how we leverage advancements in technology and tremendous amounts of data across our ecosystem, and tie it with machine learning technology and other things advancing the field of analytics. Here are some edited excerpts of that conversation. One of the things weâ??ve

article thumbnail

What is enterprise architecture? A framework for transformation

CIO

Enterprise architecture definition Enterprise architecture (EA) is the practice of analyzing, designing, planning, and implementing enterprise analysis to successfully execute on business strategies. Making it easier to evaluate existing architecture against long-term goals.

article thumbnail

Machine Learning Pipeline: Architecture of ML Platform in Production

Altexsoft

Machine learning (ML) history can be traced back to the 1950s, when the first neural networks and ML algorithms appeared. Analysis of more than 16.000 papers on data science by MIT technologies shows the exponential growth of machine learning during the last 20 years pumped by big data and deep learning advancements.

article thumbnail

ML.NET: A Robust Framework for Implementing Machine Learning in.NET Environments

Exadel

Python is irreplaceable for Machine Learning, but running Python in production can be a problem if other parts of the system are written using C#. ML.NET is a Machine Learning library for C# that helps deliver Machine Learning features in a.NET environment more quickly. That is where ML.NET can help.

article thumbnail

Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

AWS Machine Learning - AI

A generative pre-trained transformer (GPT) uses causal autoregressive updates to make prediction. Variety of tasks such as speech recognition, text generation, and question answering are demonstrated to have stupendous performance by these model architectures. Both are decoder models following similar architectural design as Chat GPT3.

AWS 92