Kubeflow Times Machine Learning — Reproducibility Step by Step

Architecting smart applications on top of Apache Spark

Here I would like to share a set of architectural guidelines for building a platform for data scientists and big data engineers that will allow them to expose analytics as services for enterprise solutions. We’ll walk through design…

Machine Learning Models Monitoring Architectures

Serving Machine Learning Model in Production — Step-by-Step Guide

On the delivery of AI to Business

Before I start I have to mention that I don’t have any prior experience of working at the head of…

Serving Machine Learning Model in Production — Step-by-Step Guide-2

What Grinds My Data Science Gears

Most of the libraries don’t care for steps of your ML Workflow after…

Data testing: requirements and levels

My name is Aleksei Chumagin, and I’m a tester at Provectus Inc. In this article, I will talk…

Active Learning, Wellies and Daisies

Besides plenty of practical benefits, we do love machine learning (ML) for the fun it brings…

Machine Learning Challenges

Machine Learning (ML) today is less of a mystery than ever, powering a diverse set of businesses, industries and public activities. Risks management, ad targeting, recommendation services, logistics, security are a few of many areas where performance rises multiple times being…