CIO

JUNE 7, 2022

Data scientists may build the ML models, but its ML engineers who implement them. This person is tasked with packing the ML model into a container and deploying to production — usually as a microservice,” says Dattaraj Rao, innovation and R&D architect at technology services company Persistent Systems. Data engineer.

Artificial Inteligence 218

Artificial Inteligence Technical Review Fractional CTO Data Engineering 218

Apiumhub

NOVEMBER 17, 2022

Clare Sudbery – Independent Technical Coach specialized in TDD, refactoring, continuous integration, and other eXtreme Programming (XP) practices. Russ Miles – Chaos Engineer Thought Leader & Author of multiple books including “Antifragile Software: Building Adaptable Software with Microservices”.

Technical Review 80

Technical Review Software Review Fractional CTO CTO Coach 80

d2iq

FEBRUARY 19, 2021

Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Apiumhub

APRIL 18, 2019

We can’t wait to attend them all: Best practices in a modern (microservices) environment by Alvaro García. Micro Frontend: the microservice puzzle extended to frontend by Audrey Neveu. Nowadays Architecture Trends, from Monolith to Microservices and Serverless by Alberto Salazar. Responsible Microservices by Nate Schutta.

Technical Review 57

Technical Review Microservices Software Review CTO Coach 57

Apiumhub

AUGUST 12, 2021

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

OpenCredo

JULY 13, 2018

We were asked to iron out some of the creases in a new Data Producer platform involving one of the Data Consumer pipelines (let’s call it Project Datatron). At first it looked like a fairly straightforward data engineering problem. We were introduced to the relevant Consumer, namely the Business Data team.

Architecture 40

Architecture Fractional CTO CTO Coach Engineering 40