MLOps Platform and services from experienced ML experts

Neu.ro platform seamlessly stitches your on-prem and cloud resources, deploys pipelines, integrates your open-source and commercial development tools. Neu.ro lets data scientists focus on what’s most important: building effective models.

2021 MLOps Platforms
Vendor Analysis Report

Neu.ro is pleased to share a new report – 2021 MLOps Platform Vendor Analysis. Developed for AI/ML leaders like you, we’ve analyzed how 10 MLOPs vendors stack up in terms of infrastructure, data management, model development, model training, tuning, and deployment.

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Intro

FEATURED EXPERT

Products

MLOPS PLATFORM

Out of the box Neu.ro spins up a full-fledged ML development environment with all the tools you need at your fingertips.

Neu.ro provides management of the infrastructure and processes for successful ML development at scale. Our team seamlessly stitches your on-prem and cloud resources, deploys pipelines, integrates your open-source and commercial development tools.

Industry reports attest that 80%+ of data science projects never make it into production while consuming far more resources and time than originally anticipated. A sound MLOps process and implementation addresses this challenge by combining AI/ML practices with DevOps to create continuous development and delivery (CI/CD) of data and ML functionality that controls the costs and de-risks delivery.

Data Collection

Model Development

Monitoring

Neu.ro

Training

Deployment

Experiment Tracking

MLOps

SOLUTIONS

It’s a crying shame that data scientists today spend so little of their time doing data science. The reality is that teams spend most of their day on data wrangling, data preparation, handling software packages and frameworks, configuring infrastructure, and integrating various components. Neu.ro solves this – it’s like having an experienced MLOps team in-house to shave months off of your development schedule.

With Neu.ro you will never have a “just read the manual” moment. Neu.ro is a managed service. This means constant support, and leaving nothing to chance. When your organization needs a new tool or methodology, we are there to operationalize it. We help you maintain every step of your ML development pipeline.

ON PREM

AWS

AZURE

GCP

VMWARE

Insights

Neu.ro brings MLOps and AI expertise to the Content Authenticity Initiative

Neu.ro is excited to join an amazing group of companies who form the Content Authenticity Initiative, an organization dedicated to the creation of a simple, extensible and distributed media provenance solution. Announced by Adobe in 2019, CAI membership includes The New York Times, the BBC, ARM, Microsoft, Qualcom, and a host of other companies focused on distribution of accurate and verifiable digital content.

With AI-driven content generation becoming an increasingly important part of the media landscape, content creators and consumers are recognizing the positive and negative impacts that technology can have on content provenance. With this in mind, Neu.ro is pleased to bring its technical expertise in AI, Machine Learning, and Deep Learning to the CAI.

…

Neu.ro Team at NVIDIA GTC

Neu.ro is honored to be presenting the future of MLOps at NVIDIA GTC, April 12-16. NVIDIA has put together an amazing lineup of AI/ML leaders including Yoshua Bengio, Geoffrey Hinton, Yann LeCun and many others.

Neu.ro's Director of Partnerships, Arthur McCallum, will present the future of MLOps in the Inception Track. His video presentation will be available for all attendees to view from April 12-16. Learn what MLOps can do for your AI strategy.

Many thanks to the NVIDIA Inception program for driving MLOps innovation.

GTC 2021 is a free conference - register today .

Designing a scalable face detection system in 2020

Introduction

Face detection is one of the core problems in Computer Vision that emerged way long before neural networks became widely used. You could think it had already been solved a long time ago. Github is full of toy repositories and even almost-production-ready frameworks on this subject.

But reality turned out to be much more complex when we ourselves started solving the mask detection problem in the beginning of March 2020 due to COVID-19.

Why mask detection is important

There arose an urgent need for social responsibility around wearing face masks. People not wearing masks in public places -…

Engineering Lab #1 — TEAM 3: “When PyTorch meets MLFlow” for Review Classification

Last week, Artyom Yushkovskyi, of Neu.ro’s MLOps engineering team joined us at the regular MLOps coffee sessions with MLOps.Community. His team recently successfully implemented a sentiment analysis solution for a large public dataset of restaurant reviews. Using an NLP approach, they were able to automate the classification of all such reviews as either positive or negative. Here are the key takeaways from this session (original article by MLOps community here).

Team 3 participants:

Artem Yushkovsky (@artemlops): MLOps Engineer @ Neu.ro
Paulo Maia (@paulomaia20): DS @ NILG.AI
Dimitrios Mangonakis (@dmangonakis): MLE @ Big 4
Laszlo Sragner (@xLaszlo): Founder @ Hypergolic

Case studies

Synthesis AI

A San Francisco-based AI infrastructure company needed robust MLOps to unblock scaling of their synthetic data platform.

Revenue Grid

An AI-centric CRM company sought to unblock production scaling of their NLP pipelines for email integration, automated sequencing and guided selling.

MegaFon

A leading telecom company needed a complete AI/ML development environment deployed within their existing cloud infrastructure. They got it within 2 months.

EMBL

The European Microbiology Laboratory advanced traditional microbiology research methods with state-of-the-art Deep Learning.

Outforz / Henkel

A retail giant sought an industry-leading Computer Vision application sufficiently robust to support it’s global scale.

Hokutake Takeyama

Japan’s leading medical supplies company sought to automate their supply chain with state-of-the-art Computer Vision.

Expert talks

Sergey Nikolenko

Machine and Deep learning, Ph.D., Chief Research Officer

Mariya Davydova

Board member at MLOps.community, Head of Product at Neu.ro

Manuel Morales

Professor of Mathematical Finance & Applied AI Researcher and Consultant

Max Prasolov

Digital Transformation expert, Researcher at UC Berkeley co-founder and CMO at Neu.ro

Constantine Goltsev

CEO of Neu.ro

Arthur McCallum

Director of Partnerships

Machine and Deep Learning Research by PhD

World-class researcher in Machine Learning, Deep Learning, Machine Learning Applications, Algorithms, Theoretical Computer Science. Sergey has authored more than 170 research papers, several books and patents, courses on machine learning, deep learning, and more. His bestselling “Deep Learning” book has become the standard source on deep learning in Russian. He also serves as Advisor for Samsung AI Lab and Head of Lab of the Steklov Institute of Mathematics at St. Petersburg.

MLOps Expertise

“Software developers and ML practitioners alike need best-in-class tools to create the best solutions” is Mariya Davydova’s credo. Her professional passion is meta-products: the ones used by domain-oriented specialists for solving their business problems, be those from the software, machine learning, or needlecraft worlds.

Having broad experience from enterprise software development through customer relationships and developer advocacy to product management, she creates best-in-class software and MLOps solutions in a diversity of domains.

Mariya’s MLOps expertise allows her to architect and build complex enterprise-level MLOps solutions that incorporate the principles of reproducibility, automation, collaboration, and accountability.

Being a proactive community leader, she participates in the management of several communities, including MLOps.community, AI Infrastructure Alliance, and Neu.ro Community.

Mariya’s functional expertise includes: MLOps, Software Development, Software Architecture, MLOps Solutions Architecture, Customer Relationship, Agile.

ML/DL Research Meets Real World Implementations

Manuel Morales, PhD, is Senior AI Advisor to Neu.ro, focusing on finance, banking and Fintech. Professor Morales brings extensive experience in both research and applied ML to the Neu.ro team.

He serves as an Associate Professor of Financial & Actuarial Mathematics in the Department of Mathematics and Statistics at the University of Montreal, where his current research interests include Applied ML in banking and in responsible investment.

Formerly, Professor Morales served as Chief AI Scientist at the National Bank of Canada, where he led the scientific efforts of the bank’s strategy to leverage AI technologies across all verticals. While playing a leading role in the AI transformation initiative of the bank, he had the opportunity to work on a wide variety of projects from wealth management to retail banking applications.

Since 2018, Dr. Morales has also been the General Director of the Fin –ML Network.

The Fin-ML network or Machine Learning in Finance, was created to develop the global competitiveness of the Canadian finance sector by promoting and supporting the development and use of innovative information technology processes and solutions in the field of innovative machine learning technology in quantitative finance and financial business analytics.

Manuel’s research interests include Representation Learning in banking, Deep Learning methods in high frequency market surveillance, explainability in the context of model governance and leveraging alternative data to assess environmental, societal and governance (ESG) factors in the context of responsible investment

AI-Driven Digital Transformation Expert

Max Prasolov is a customer success-oriented data science executive specializing in guiding enterprises through AI-driven digital transformation processes. He brings vast experience in the identification of new market niches for cutting-edge AI technologies to the clients he serves.

Max has extensive and diversified digital transformation experience in Healthcare, Financial Services, Retail & eCommerce, Media, Telecommunication, Metallurgy, Mining. He supports this work with a solid background in Data Science, Machine Learning, Visual Data, and CGI Multimedia.

A C-Level visionary with a strong ability to orchestrate single effort and multifunction activities and support large enterprises through digital transformation challenges, Max is known as an ardent and motivational mentor for modernizing large-scale organizations and startups.

Functional Expertise: Digital Transformation Consulting, Data-Driven StoryTelling, AI and MLOps Solutions & Services.

Making Tech Work for Business

A serial entrepreneur, Constantine has created and led digital product companies that push the technological envelope for over 20 years.

Stemming from a background in applied math, statistical analysis and algorithmic agents, and a series of successful products in online video and AdTech, Constantine brings both technical proficiency and business acumen to Neu.ro’s leadership team.

In client relationships, Constantine is a clear voice for data-centric decision making. He focuses on assisting stakeholders plan and execute AI strategies, defining project scope and matching the appropriate AI/ML technology to each business case.

Constantine is a passionate advocate for responsible, reproducible and ethical AI.

AI Transformation Takes a Village

Arthur is an AI Strategist focusing on Digital Transformation, hardware and cloud infrastructure. Working with industry leaders in the GPU, cloud services and ML software sectors, he is dedicated to helping startups and enterprises find the hardware and cloud solutions they need to responsibly scale AI Transformation. Arthur takes a hands-on approach to engagement of tech and business teams to facilitate the development of specific AI/ML use cases, educate stakeholders, select ML technologies, and integrate AI/ML solutions into business processes.

Arthur’s partnership mission is focused on growing Neu.ro’s ecosystem to include the world’s most innovative technology partners, establishing a network that provides our clients with all the resources, technologies and people required to effectively and safely scale their AI strategies.

Arthur is passionate about learning and is most happy in a room of smarter people developing solutions to hard problems.

Certifications:
MIT Sloan Executive Education – Digital Transformation
Columbia University Executive Education – Executive Data Scientist
AWS Fundamentals Specialization