MLOps community meetup #60! Last Wednesday we talked to Vishnu Prathish, Director Of Engineering, AI Products, Innovyze. //Abstract The way Data Science is done is changing. Notebook sharing and collaboration were messy and there was minimal visibility or QA into the model deployment process. Vishnu will talk about building an ops platform that deploys hundreds of models at-scale every month. A platform that supports typical features of MLOps (CI/CD, Separated QA, Dev and PROD environment, exper...
Apr 16, 2021•58 min•Season 1Ep. 60
Coffee Sessions #34 with Geoff Sims of Atlassian, Machine Learning at Atlassian. //Abstract As one of the world's most visible software companies, Atlassian's vast data and deep product suite pose an interesting MLOps challenge, and we're grateful to Geoff for taking us behind the curtain. //Bio Geoff is a Principal Data Scientist at Atlassian, the software company behind Jira, Confluence & Trello. He works with the product teams and focuses on delivering smarter in-product experiences and r...
Apr 12, 2021•59 min•Season 1Ep. 34
MLOps community meetup #59! Last Wednesday was the celebration of the MLOps Community 1 Year Anniversary! This has been a conversion of Demetrios Brinkmann, David Aponte and Vishnu Rachkonda! //Abstract Over the past year Demetrios, David and Vishnu have interviewed many of the top names in MLOps. During this time they have been able to apply these learnings at their jobs and see what works for them. In this one year anniversary meetup the three of them will discuss some of the most impacting ad...
Apr 09, 2021•59 min•Season 1Ep. 59
Coffee Sessions #33 with Sarah Catanzaro of Amplify Partners, MLOps Investments. //Bio Sarah Catanzaro is a Partner at Amplify Partners, where she focuses on investing in and advising high potential startups in machine intelligence, data management, and distributed systems. Her investments at Amplify include startups like RunwayML, Maze Design, OctoML, and Metaphor Data among others. Sarah also has several years of experience defining data strategy and leading data science teams at startups and ...
Apr 06, 2021•46 min•Season 1Ep. 33
MLOps community meetup #58! Last Wednesday we talked to Ben Wilson, Practice Lead Resident Solutions Architect, Databricks. Model Monitoring Deep Dive with the author of Machine Learning Engineering in Action. It was a pleasure getting to talk to Ben about difficulties in monitoring in machine learning. His expertise obviously comes from experience and as he said a few times in the meetup, I learned the hard way over 10 years as a data scientist so you don't have to! Ben was also kind enough to ...
Apr 04, 2021•53 min•Season 1Ep. 58
MLOps community meetup #57! Last Wednesday we talked to Josh Tobin, Founder, Stealth-Stage Startup. // Abstract: Machine learning is quickly becoming a product engineering discipline. Although several new categories of infrastructure and tools have emerged to help teams turn their models into production systems, doing so is still extremely challenging for most companies. In this talk, we survey the tooling landscape and point out several parts of the machine learning lifecycle that are still und...
Mar 26, 2021•56 min•Season 1Ep. 57
Coffee Sessions #32 with D. Sculley of Google, The Godfather Of MLOps. //Bio D is currently a director in Google Brain, leading research teams working on robust, responsible, reliable and efficient ML and AI. In his time at Google, D worked on nearly every aspect of machine learning, and have led both product and research teams including those on some of the most challenging business problems. // Links to D. Sculley's Papers ML Test Score: https://research.google/pubs/pub46555/ Machine Learning:...
Mar 23, 2021•52 min•Season 1Ep. 32
MLOps community meetup #56! Last Wednesday we talked to Daniel Stahl, Head of Data and Analytic Platforms, Regions Bank. // Abstract: The Data Science practice has evolved significantly at Regions, with a corresponding need to scale and operationalize machine learning models. Additionally, highly regulated industries such as finance require a heightened focus on reproducibility, documentation, and model controls. In this session with Daniel Stahl, we will discuss how the Regions team...
Mar 19, 2021•1 hr 5 min•Season 1Ep. 56
MLOps community meetup #55! Last Wednesday we talked to Igor Lushchyk, Data Engineer, Adyen. // Abstract: Building Data Science and Machine Learning platforms at a scale-up. Having the main difficulty in finding correct processes and basically being a toddler who learns how to walk on a steep staircase. The transition from homegrown platform to open source solutions, supporting old solutions and maturing them with making data scientists happy. // Bio: Igor is a software engineer wi...
Mar 12, 2021•58 min•Season 1Ep. 55
MLOps community meetup #54! Last Wednesday we talked to Laszlo Sragner, Founder, Hypergolic. // Abstract: How my experience in quant finance and software engineering influenced how we ran ML at a London Fintech Startup. How to solve business problems with incremental ML? What's the difference between academic and industrial ML? // Bio: Laszlo worked as a quant researcher at multiple investment managers and as a DS at the world's largest mobile gaming company. As Head of Data Science at Arkera, h...
Mar 05, 2021•58 min•Season 1Ep. 54
This is a deep dive into the most recent MLOps Engineering Labs from the point of view of Team 3. // Diagram Link: https://github.com/dmangonakis/mlops-lab-example-yelp --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Las...
Mar 02, 2021•1 hr 4 min•Season 1Ep. 31
MLOps community meetup #53! Last Wednesday we talked to Krishna Gade, CEO & Co-Founder, Fiddler AI. // Abstract: Training and deploying ML models have become relatively fast and cheap, but with the rise of ML use cases, more companies and practitioners face the challenge of building “Responsible AI.” One of the barriers they encounter is increasing transparency across the entire AI lifecycle to not only better understand predictions, but also to find problem drivers. In this session with Kri...
Mar 01, 2021•57 min•Season 1Ep. 53
This is a deep dive into the most recent MLOps Engineering Labs from the point of view of Team 1. // Diagram Link: https://github.com/mlops-labs-team1/engineering.labs#workflow --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Alexey on LinkedIn: htt...
Feb 23, 2021•1 hr•Season 1Ep. 30
MLOps community meetup #52! Last Wednesday we talked to Luke Feeney and Gavin Mendel-Gleason, TerminusDB. // Abstract: A look at the open-source 'Git for Data' landscape with a focus on how the various tools fit into the pipeline. Following that scene-setting, we will delve into how and why TerminusDB builds a revision control database from the ground up. // Takeaways - Understanding the 'git for data' offering and landscape - See how to technically approach a revision control database implement...
Feb 19, 2021•58 min•Season 1Ep. 52
MLOps community meetup #51! Last Wednesday we talked to Pamela Jasper, AI Ethicist, Founder, Jasper Consulting Inc. // Abstract: One of the challenges to the widespread adoption of AI Ethics is not only its integration with MLOps, but the added processes to embed ethical principles will slow and impede Innovation. I will discuss ways in which DS and ML teams can adopt Agile practices for Responsible AI. // Bio: Pamela M. Jasper, PMP is a global financial services technology leader with over 30 y...
Feb 12, 2021•1 hr 7 min•Season 1Ep. 51
Coffee Sessions #29 with Jet Basrawi of Satalia, Culture and Architecture in MLOps. //Bio Jet started his career in technology as a game designer but became interested in programming. He found he loved it. It was endlessly challenging and deeply enjoyable "Flow" activity. It was also nice to be in demand and earn a living. In the last several years, Jet been passionate about DevOps as a key strategic practice. About a year ago, he came into the AI world and it is a great place to be for someone ...
Feb 08, 2021•54 min•Season 1Ep. 29
MLOps community meetup #50! Last Wednesday we talked to Michael Del Balso, Willem Pienaar and David Aronchick, // Abstract: The MLOps tooling landscape is confusing. There’s a complicated patchwork of products and open-source software that each cover some subset of the infrastructure requirements to get ML to production. In this session - we’ll focus on the two most important platforms: model management platforms and feature stores. Model management platforms such as Kubeflow help you get models...
Feb 05, 2021•57 min•Season 1Ep. 50
MLOps community meetup #49! Last Wednesday we talked to Lak Lakshmanan, Data Analytics and AI Solutions, Google Cloud. // Abstract: Design patterns are formalized best practices to solve common problems when designing a software system. As machine learning moves from being a research discipline to a software one, it is useful to catalogue tried-and-proven methods to help engineers tackle frequently occurring problems that crop up during the ML process. In this talk, I will cover five patterns (W...
Feb 02, 2021•57 min•Season 1Ep. 49
Coffee Sessions #28 with Charlie You of Workday, Lessons learned from hosting the Machine Learning Engineered podcast //Bio Charlie You is a Machine Learning Engineer at Workday and the host of ML Engineered, a long-form interview podcast aiming to help listeners bring AI out of the lab and into products that people love. He holds a B.S. in Computer Science from Rensselaer Polytechnic Institute and previously worked for AWS AI. Charlie is currently working as a Machine Learning Engineer at Workd...
Jan 29, 2021•1 hr 5 min•Season 1Ep. 28
Coffee Sessions #27 with Noah Gift of Pragmatic AI Labs, Practical MLOps // A “Gift” from Above This week, Demetrios and Vishnu got to spend time with inimitable Noah Gift. Noah is a data science educator, who teaches at Duke, Northwestern, and many other universities, as well as a technical leader through his company Pragmatic AI Labs and past companies. His bio alone would take up this section of the newsletter, so we invite you to check it out here, as well as the rest of his educationa...
Jan 26, 2021•59 min•Season 1Ep. 27
MLOps community meetup #48! Last Wednesday, we talked to Manoj Agarwal, Software Architect at Salesforce. // Abstract: Serving machine learning models is a scalability challenge at many companies. Most applications require a small number of machine learning models (often < 100) to serve predictions. On the other hand, cloud platforms that support model serving, though they support hundreds of thousands of models, provision separate hardware for different customers. Salesforce has a uniq...
Jan 24, 2021•56 min•Season 1Ep. 48
**Private data, Data Science friendly** Data Scientists are always eager to get their hands on more data, in particular, if that data has any value that can be extracted. Nevertheless, in real-world situations, data does not exist in the abundance that we thought existed, in other situations, the data might exist, but not possible to share it with different entities due to privacy concerns, which makes the work of data scientists not only hard, but sometimes even impossible. // Abstract: In the ...
Jan 21, 2021•42 min•Season 1Ep. 9
Coffee Sessions #26 with Vishnu Rachakonda of Tesseract Health, Daniel Galinkin of iFood, Matias Dominguez of Rappi & Simarpal Khaira of Intuit, Feature Store Master Class. //Bio Vishnu Rachakonda Machine Learning Engineer at Tesseract Health. Coffee sessions co-host but this time his role is one of the all-stars guest speakers. Daniel Galinkin One of the co-founders of Hekima, one of the first companies in Brazil to work with big data and data science, with over 10 years of experience in th...
Jan 19, 2021•1 hr 6 min•Season 1Ep. 26
MLOps community meetup #47! Last Wednesday, we talked to Adrià Romero, Founder and Instructor at ProductizeML. // Abstract: In this talk, we tackled: - Motivations and mission behind ProductizeML. - Common friction points and miscommunication between technical and management/product teams, and how to bridge these gaps. - How to define ML product roadmaps, (and more importantly, how to get it signed off by all your team). - Best practices when managing the end-to-end ML lifecyc...
Jan 18, 2021•51 min•Season 1Ep. 47
The revolution of Federated Learning - And we're back with another episode of the podcast When Machine Learning meets Privacy! For the episode #8 we've invited Ramen Dutta, a member of our community and founder of TensoAI. // Abstract: In this episode, Ramen explain us the concept behind Federated Learning, all the amazing benefits and it's applications in different industries, particularly in agriculture. It's all about not centralizing the data, sound awkward? Just listen to the episode....
Jan 14, 2021•29 min•Season 1Ep. 8
Coffee Sessions #25 with Marian Ignev of CloudStrap.io & SashiDo.io, Most Underrated MLOps Topics. //Bio Marian a passionate entrepreneur, backend dude & visionary. These are the three main things described to Marian very well: Marian's everyday routines include making things happen and motivating people to work hard and learn all the time because I think success is a marathon, not just a sprint! Marian loves to communicate with bright creative minds who want to change things. His...
Jan 12, 2021•54 min•Season 1Ep. 25
MLOps community meetup #46! Last Wednesday, we talked to Hendrik Brackmann, Director of Data Science and Analytics at Tide. // Abstract: Tide is a U.K.-based FinTech startup with offices in London, Sofia, and Hyderabad. It is one of the first, and the largest business banking platform in the UK, with over 150,000 SME members. As of 2019, one of Tide’s main focuses is to be data-driven. This resulted in the forming of a Data Science and Analytics Team with Hendrik Brackmann at its head. Let's wit...
Jan 08, 2021•58 min•Season 1Ep. 46
Coffee Sessions #24 with Sara Robinson of Google, Machine Learning Design Patterns co-hosted by Vishnu Rachakonda. //Bio Sara is a Developer Advocate for Google Cloud, focusing on machine learning. She inspires developers and data scientists to integrate ML into their applications through demos, online content, and events. Before Google, she was a Developer Advocate on the Firebase team. Sara has a Bachelor’s degree from Brandeis University. When she’s not writing code, she can be found on a spi...
Dec 29, 2020•1 hr•Season 1Ep. 24
Coffee Sessions #23 with Todd Underwood of Google, Followups from OPML Talks on ML Pipeline Reliability co-hosted by Vishnu Rachakonda. //Bio Todd is a Director at Google and leads Machine Learning for Site Reliability Engineering Director. He is also Site Lead for Google’s Pittsburgh office. ML SRE teams build and scale internal and external ML services and are critical to almost every Product Area at Google. Before working at Google, Todd held a variety of roles at Renesys. He was in cha...
Dec 22, 2020•1 hr 12 min•Season 1Ep. 23
MLOps community meetup #45! Last Wednesday, we talked to Joe Reis, CEO/Co-Founder of Ternary Data. // Abstract: The fact is that most companies are barely doing BI, let alone AI. Joe discussed ways for companies to build a solid data foundation so they can succeed with machine learning. This meetup covers the continuum from cloud data warehousing to MLOps. // Bio: Joe is a Data Engineer and Architect, Recovering Data Scientist, 20 years in the data game. Joe enjoys helping companies make s...
Dec 20, 2020•54 min•Season 1Ep. 45
