Coffee Sessions #39 with Stephen Galsworthy of Quby, MLOps: A leader's perspective. //Abstract //Bio Dr. Stephen Galsworthy is a data leader skilled at building high-performing teams and passionate about developing data-powered products with lasting impact on users, businesses, and society. Most recently he was the Chief Data and Product Officer at Quby, an Amsterdam-based tech company offering data-driven energy services. He oversaw its transformation from a hardware-based business to a digital...
May 18, 2021•54 min•Season 1Ep. 39
MLOps community meetup #63! Last Wednesday we talked to Felipe Campos Penha, Senior Data Scientist, Cargill. //Abstract Can one learn anything useful by creating content online? The usual answer is a sounding YES. But what about live coding an MLOps project on Twitch? Can anything good come out of it? //Bio Felipe Penha creates content about Data Science regularly on the Data Science Bits channel on YouTube and Twitch. He has 8+ years of experience with hands-on data-related work, starting with ...
May 14, 2021•50 min•Season 1Ep. 63
MLOps community meetup #62! Last Wednesday we talked to Oguzhan Gencoglu, Co-founder & Head of AI, Top Data Science. //Abstract Starting the AI adoption with AI Proof-of-Concepts (PoCs) is the most common choice for most companies. Yet, a significant percentage of AI PoCs do not make it into production whether they were successful or not. Furthermore, running yet another AI PoC follows the law of diminishing returns in various aspects. This talk will revolve around this theme. //Bio Oguzhan ...
May 10, 2021•56 min•Season 1Ep. 62
Coffee Sessions #38 with Adam Sroka of Origami Energy, Organisational Challenges of MLOps. //Abstract Deploying data science solutions into production is challenging for both small and large organizations. From platform and tooling wars to architecture and design pattern trade-offs it can get overwhelming for inexperienced teams. Furthermore, many organizations will only go through the painful discovery process once. Adam will share some of his experiences from consulting and leading data teams ...
May 07, 2021•55 min•Season 1Ep. 38
MLOps community meetup #61! Last Wednesday we talked to Lex Beattie, Michael Munn, and Mike Moran. //Abstract We started out talking about some of the main bottlenecks they have encountered over the years of trying to push data products into production environments. Then things started to heat up as we dove into the topic of monitoring ML and inevitably the word explainability started being thrown around. Turns out Lex is currently doing a Ph.D. on the subject so there was much to talk about. We...
May 03, 2021•53 min•Season 1Ep. 61
Coffee Sessions #37 with Ariel Biller of ClearML, MLOps Memes. //Abstract The Meme king of MLOps joins us to talk about why we need more MLOps memes and how he got so damn good at being able to zoom out and see things from a metta level them make a meme about it! //Bio A researcher first, developer second, in the last 5 years Ariel worked on various projects from the realms of quantum chemistry, massively parallel supercomputing, and deep-learning computer vision. With AllegroAi, he helped build...
Apr 30, 2021•1 hr 1 min•Season 1Ep. 37
Coffee Sessions #36 with Luigi Patruno of 2U, Luigi in Production Part 2. //Abstract Learning Voraciously: We talk a lot in the community about how to learn and upskill in an efficient way. Luigi provided great insight into how he applies certain principles to his learning practices. One tip he shared is to rigorously read and digest books. Luigi himself has used books to address his knowledge gaps in areas like product, finance, etc. I appreciated the emphasis on books. A lot of the reason we f...
Apr 23, 2021•59 min•Season 1Ep. 36
Coffee Sessions #35 with Nick Masca of Marks and Spencer, War Stories Productionising ML. //Abstract A conversation with MLOps war stories. Better said, a war story conversation. The kind that informs modern MLOps best practices. Nick shared how to make MLOps organizational changes at large companies. I loved one tidbit he mentioned--"it's an evolution, not a revolution". That's a frank observation about the speed of practical change. As we all know it doesn't happen overnight. Another great lea...
Apr 19, 2021•51 min•Season 1Ep. 35
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 designed an...
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 with more than 1...
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 Laszlo on LinkedIn https://www....
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 educational cont...
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 unique cha...
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
