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MLOps.community

Relaxed Conversations around getting AI into production, whatever shape that may come in (agentic, traditional ML, LLMs, Vibes, etc)

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All Episodes

00:55:35

10 Types of Features your Location ML Model is...

MLOps.community ·

2021/10/07

Coffee Sessions #58 with Anne Cocos, 10 Types of Features your Location ML Model is Missing. // Abstract Machine learning on geographic data is relatively under-studied in comparison to ML on other formats like images or graphs. But geographic data is prevalent across a wide variety of domains (although many practitioners may not think of it that way). Clearly, any dataset with `latitude` and `longitude` columns can be viewed as geographic data, but also any dataset with a `zipcode`, `city`,

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00:55:27

The Future of ML and Data Platforms // Michael Del...

MLOps.community ·

2021/10/01

Coffee Sessions #57 with Michael Del Balso and Erik Bernhardsson, The Future of ML and Data Platforms. // Abstract Machine learning, data analytics, and software engineering are converging as data-intensive systems become more ubiquitous. Erik Bernhardsson, ex-CTO at Better and former Spotify machine learning lead, and Mike Del Balso, CEO at Tecton and former Uber machine learning lead and co-creator of Michelangelo sit down to chat with us today. These two jammed with us about building machine

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00:52:18

A Few Learnings from Building a Bootstrapped MLOps...

MLOps.community ·

2021/09/27

Soumanta wouldn't claim they've reached where they want to and they're still learning, so he's happy sharing successes as well as failures at Yugen.ai. // Abstract Determining Minimum Achievable Goals helps Yugen.ai ensure a significant amount of focus on value-added and impact before diving deep into solutions & building ML Systems. In this episode, Soumanta discusses Balancing ML Development vs Ops and Monitoring efforts while scaling plus their focus on improvements in small

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00:48:06

Learning and Teaching MLOps Applications // Salwa...

MLOps.community ·

2021/09/21

Coffee Sessions #55 with Salwa Muhammad, Learning and Teaching MLOps Applications. //Abstract Salwa shared her perspective on how FourthBrain and all learners can keep their education strategy fresh enough for the current zeitgeist. Furthermore, Salwa, Demetrios, and Vishnu talked about principles of effective learning that are important to keep in mind while embarking on any educational journey. This was a great conversation with a lot of practical tips that we hope you all listen to! //

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00:48:40

Machine Learning SRE // Niall Murphy // MLOps Coffee...

MLOps.community ·

2021/09/10

Coffee Sessions #54 with Niall Murphy, Machine Learning SRE. //Abstract SRE is making its way into the machine learning world. Software engineering for machine learning requires reliability, performance, and maintainability. Site reliability engineering is the field that deals with reliability and ensuring constant, real-time performance. Niall Murphy, most recently Global Head of SRE at Microsoft Azure, helps us understand what SRE can do for modern ML products and teams. Building machine

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00:37:58

MLOps Insights // David Aponte-Demetrios...

MLOps.community ·

2021/09/07

Coffee Sessions #53 with David Aponte, Demetrios Brinkmann, and Vishnu Rachakonda, MLOps Insights. //Abstract MLOps Insights from MLOps community core organizers Demetrios Brinkmann, Vishnu Rachakonda, and David Aponte. In this conversation the guys do a deep dive on testing with respect to MLOps, talk about what they have learned recently around the ML field, and what new things are happening with the MLOps community. //Bio David Aponte David is one of the organizers of the MLOps Community. He is

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00:49:58

Vector Similarity Search at Scale // Dave Bergstein...

MLOps.community ·

2021/08/31

Coffee Sessions #52 with Dave Bergstein, Vector Similarity Search at Scale. //Abstract Ever wonder how Facebook and Spotify now seem to know you better than your friends? Or why the search feature in some products really “gets” you while in other products it feels stuck in the '90s? The difference is vector search— a method of indexing and searching through large volumes of vector embeddings to find more relevant search results and recommendations. Dave Bergstein, the Director of Product at

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00:52:31

ML Security: Why should you care? // Sahbi Chaieb //...

MLOps.community ·

2021/08/17

Coffee Sessions #51 with Sahbi Chaieb, ML security: Why should you care? //Abstract Sahbi, a senior data scientist at SAS, joined us to discuss the various security challenges in MLOps. We went deep into the research he found describing various threats as part of a recent paper he wrote. We also discussed tooling options for this problem that is emerging from companies like Microsoft and Google. // Bio Sahbi Chaieb is a Senior Data Scientist at SAS, he has been working on designing, implementing,

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00:47:55

Creating MLOps Standards // Alex Chung and Srivathsan...

MLOps.community ·

2021/08/12

Coffee Sessions #50 with Alex Chung and Srivathsan Canchi, Creating MLOps Standards. // Abstract With the explosion in tools and opinionated frameworks for machine learning, it's very hard to define standards and best practices for MLOps and ML platforms. Based on their building AWS SageMaker and Intuit's ML Platform respectively, Alex Chung and Srivathsan Canchi talk with Demetrios and Vishnu about their experience navigating "tooling sprawl". They discuss their efforts to solve this problem

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00:52:02

Aggressively Helpful Platform Teams // Stefan...

MLOps.community ·

2021/08/10

Coffee Sessions #49 with Stefan Krawczyk, Aggressively Helpful Platform Teams. //Abstract At Stitch Fix there are 130+ “Full Stack Data Scientists” who in addition to doing data science work, are also expected to engineer and own data pipelines for their production models. One data science team, the Forecasting, Estimation, and Demand team were in a bind. Their data generation process was causing them iteration & operational frustrations in delivering time-series forecasts for the business. the

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00:52:15

Tour of Upcoming Features on the Hugging Face Model...

MLOps.community ·

2021/07/27

Coffee Sessions #48 with Julien Chaumond, Tour of Upcoming Features on the Hugging Face Model Hub. //Abstract Julien Chaumond’s Tour of Upcoming Features on the Hugging Face Model Hub. Our MLOps community guest in this episode is Julien Chaumond the CTO of Hugging Face - every data scientist’s favorite NLP Swiss army knife. Julien, David, and Demetrios spoke about many topics including: Infra for hosting models/model hubs Inference widgets for companies with CPUs & GPUs (for companies) Auto NLP

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00:57:54

Fast.ai, AutoML, and Software Engineering for ML:...

MLOps.community ·

2021/07/15

Coffee Sessions #47 with Jeremy Howard, fast.ai, AutoML, Software Engineering for ML. //Abstract Advancement in ML Workflows: You've been around the ML world for long enough to have seen how much workflows, tooling, frameworks, etc. have matured and allowed for greater scale and access. We'd love to reflect on your personal journey in this regard and hear about your early experiences putting models into production, as well as how you appreciate/might improve the process now. Data Professional

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00:56:43

Learning from 150 Successful ML-enabled Products at...

MLOps.community ·

2021/07/13

Coffee Sessions #46 with Pablo Estevez, What We Learned from 150 Successful ML-enabled Products at Booking.com. //Abstract While most of the Machine Learning literature focuses on the algorithmic or mathematical aspects of the field, not much has been published about how Machine Learning can deliver meaningful impact in an industrial environment where commercial gains are paramount. We conducted an analysis on about 150 successful customer-facing applications of Machine Learning, developed by

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00:53:41

Machine Learning in Cyber Security // Monika...

MLOps.community ·

2021/07/06

MLOps community meetup #70! Last Wednesday, we talked to Monika Venckauskaite, Senior Machine Learning Engineer at Vinted. //Abstract One of the areas, that is the most transformed by ML these years is cybersecurity. Traditionally, SIEM (Security Intelligence and Event Management) is performed by human analysts. However, as the cyber powers and tools of the world are growing, we need more and more of these specialists. The entire area of cybersecurity is experiencing a shortage of talent. This is

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00:53:34

Enterprise Security and Governance MLOps // Diego...

MLOps.community ·

2021/07/02

Coffee Sessions #45 with Diego Oppenheimer of Algorithmia, Enterprise Security and Governance MLOps. //Abstract MLOps in the enterprise is difficult due to security and compliance. In this MLOps Coffee Session, the CEO of Algorithmia, Diego talks to us about how we can better approach MLOps within the enterprise. This is an introduction to essential principles of security in MLOps and why it is crucial to be aware of security best practices as an ML professional. // Bio Diego Oppenheimer is

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00:50:51

Autonomy vs. Alignment: Scaling AI teams to deliver...

MLOps.community ·

2021/06/30

Coffee Sessions #44 with Grant Wright of SEEK Ltd., Autonomy vs. Alignment: Scaling AI Teams to Deliver Value. /Abstract Setting AI teams up for success can be difficult, especially when you’re trying to balance the need to provide teams with autonomy to innovate and solve interesting problems while ensuring they are aligned to the organizations' strategy. Operating models, rituals and processes can really help to set teams up for success; but, there is no right answer, and as you scale and

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00:57:36

How Pinterest Powers Image Similarity // Shaji...

MLOps.community ·

2021/06/29

In this Machine Learning System Design Review, Shaji Chennan Kunnummel walks us through the system design for Pinterest’s near-real-time architecture for detecting similar images. We discuss their usage of Kafka, Flink, rocksdb, and much more. Starting with the high-level requirements for the system, we discussed Pinterest’s focus on debuggability and an easy transition from their batch processing system to stream processing. We then touch on the different system interfaces and components involved

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00:51:54

Engineering MLOps // Emmanuel Raj // MLOps Meetup #69

MLOps.community ·

2021/06/28

MLOps community meetup #69! Last Wednesday we talked to Emmanuel Raj, Senior Machine Learning Engineer at TietoEvry. //Abstract The talk focuses on simplifying/demystifying MLOps, encourages others to take steps to learn this powerful SE method. We also talked about Emmanuel's journey in ML engineering, the evolution of MLOps, daily life, and SE problems, and what's next in MLOps (fusion of AIOps, EU AI regulations impact on MLOps workflow, etc). //Bio Emmanuel Raj is a Finland-based Senior

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00:57:26

Project/Product Management for MLOps // Korri Jones -...

MLOps.community ·

2021/06/21

MLOps community meetup #68! Last Wednesday we talked to Veselina Staneva of TeachableHub, Simarpal Khaira of Intuit, and Korri Jones of Chick-fil-A, Inc. //Abstract Building, Designing, or even just casting the vision for MLOps for your company, whether a large corporation or an agile start-up up, shouldn't be a nigh-impossible task. Complex, but not an impossible mountain to climb. In this meetup, we talked about the steps necessary to unlock the potential of data science for your organization,

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00:47:19

Maturing Machine Learning in Enterprise // Kyle...

MLOps.community ·

2021/06/15

Coffee Sessions #43 with Kyle Gallatin of Etsy, Maturing Machine Learning in Enterprise. //Abstract The definition of Data Science in production has evolved dramatically in recent years. Despite increasing investments in MLOps, many organizations still struggle to deliver ML quickly and effectively. They often fail to recognize an ML project as a massively cross-functional initiative and confuse deployment with production. Kyle will talk about both the functional and non-functional requirements of

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514 results

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