Subscribe • Previous Issues Ratio of Data Scientists to Data Engineers A fun topic of discussion among leaders of data teams is the ratio between the number of data scientists and data engineers. There is no ideal answer. It really depends on the tools and infrastructure you have in place, the maturity and availability of use casesContinue reading “Practical Reinforcement Learning and Differential Privacy”
Author Archives: Ben Lorica
Ratio of Data Scientists to Data Engineers
As companies get more proficient in using data and AI to drive decision making and operations, team members with disparate backgrounds – analysts, product mangers, decision makers – begin using data on a regular basis. But when they’re first starting out, the requisite data may not be in place, and data processing and analysis tendContinue reading “Ratio of Data Scientists to Data Engineers”
Locating Machine Learning Engineers
Subscribe • Previous Issues Where Do Machine Learning Engineers Work? About five years ago we published a post that highlighted the emergence of a role focused on making data science work in production. At the time we noticed job postings (mainly in the SF Bay Area) that used the title “machine learning engineer” to describe individuals skilledContinue reading “Locating Machine Learning Engineers”
Where Do Machine Learning Engineers Work?
With interest in MLOps surging, companies are bound to reassess their tools, as well as the composition of their data and ML teams. About five years ago we published a post that highlighted the emergence of a role focused on making data science work in production. We were prompted by job postings (in the SFContinue reading “Where Do Machine Learning Engineers Work?”
2022 Trends in Data and AI
Subscribe • Previous Issues FREE Report: Trends in Data, Machine Learning, and AI This short guide identifies trends that will be relevant to organizations across all industries and sectors over the next 12-18 months. Download What is Graph Intelligence? In a new post with Leo Meyerovich of Graphistry, we highlight the current state of Graph Intelligence, aContinue reading “2022 Trends in Data and AI”
2022 Trends Report: Data, Machine Learning, and AI
By Ben Lorica, Mikio Braun, and Jenn Webb. In this short report, we list key trends in big data, machine learning, and AI, with a bias toward items that will impact companies and organizations across all sectors over the next 12-18 months. Tools to help companies put Data and AI to work are definitely gettingContinue reading “2022 Trends Report: Data, Machine Learning, and AI”
What is Graph Intelligence?
How and why the best companies are adopting Graph Visual Analytics, Graph AI, and Graph Neural Networks. By Leo Meyerovich and Ben Lorica. [A version of this post originally appeared on the Graphistry blog.] In this post, we highlight the current state of Graph Intelligence, a new technology category around new tools and techniques forContinue reading “What is Graph Intelligence?”
Data Remains the Key Challenge In Computer Vision Projects
Datagen recently surveyed about 300 professionals in computer vision about the value of data. The survey comes at a time of renewed focus on the importance of tools for helping ML teams address data related challenges. Data-centric AI represents a recent shift among researchers, away from focusing on models and toward the underlying data used inContinue reading “Data Remains the Key Challenge In Computer Vision Projects”
Experimentation Tools; Surge in MLOps; 2021 Books
Subscribe • Previous Issues Data Exchange podcast Modern Experimentation Platforms: Che Sharma is the founder and CEO of Eppo, an experimentation framework that integrates with modern data platforms (lakehouses and cloud data warehouses). Investors and engineers have created an abundance of companies that specialize in ML infrastructure and MLOps, while applications like experimentation have received little attention.Continue reading “Experimentation Tools; Surge in MLOps; 2021 Books”
One Simple Graphic: Interest in MLOps is surging
The overall job market in the U.S. has recovered from the depths of the pandemic. In the area of “machine learning”, demand for MLOps talent appears to be growing rapidly. This could be an early indicator that machine learning and AI initiatives are beginning to graduate from R&D projects and prototypes, into production systems: RelatedContinue reading “One Simple Graphic: Interest in MLOps is surging”