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PODCAST

MLOps.community

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

technology

All Episodes

00:58:42

Real-time Machine Learning with Chip Huyen // MLOps...

MLOps.community ·

2022/11/22

MLOps Coffee Sessions #133 {Podcast BTS} with Chip Huyen, Real-time Machine Learning with Chip Huyen co-hosted by Vishnu Rachakonda. // Abstract Forcing functions and how you can supercharge your learning by putting yourself into a situation where you know you either have a responsibility to others to learn or accountability on you so you have to learn. It's not that hard when you think about streaming machine learning. It's not that big of a mental barrier to cross. It is simple in theory but

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01:00:56

What is Data / ML Like on League? // Ian Schweer //...

MLOps.community ·

2022/11/15

MLOps Coffee Sessions #132 {Podcast BTS} with Ian Schweer, What is Data / ML Like on League? co-hosted by Skylar Payne. // Abstract If you're not an avid gamer yourself, you have never really seen how ML might be used in the gaming space. It's so interesting to see the things that are different like full stories of players' games from start to finish. // Bio On the surface, Ian is an excellent developer who gets things done. Underneath, he is much more. Ian is a reliable and trustworthy teammate

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00:51:59

Let's Continue Bundling into the Database // Ethan...

MLOps.community ·

2022/11/08

MLOps Coffee Sessions #131 {Podcast BTS} with Ethan Rosenthal, Let's Continue Bundling into the Database co-hosted by Mike Del Balso. // Abstract The relationship between ML Engineers and Product Managers is something that we don't talk about enough. We've got to get this right. If we don't get this right, either you're not focusing on the business problems in the right way or the Product Managers are not going to understand the tech appropriately to help make the right decisions. // Bio Ethan

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00:44:43

MLOps for Ad Platforms // Andrew Yates // MLOps...

MLOps.community ·

2022/10/31

MLOps Coffee Sessions #130 {Podcast BTS} with Andrew Yates, Adversarial MLOps on Other People's Money: Lessons Learned from Ad Tech co-hosted by Abi Aryan. // Abstract Design ML to be components in a larger system with stable interfaces is not tracible to monitor the entire stack as a black box. You need intermediate ground-truth signals. Ads are designed in this way. You can go from profitable to non-profitable real quick with ads. This will determine whether your company is around a year or

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00:49:59

Voice and Language Tech // Catherin Breslin // Coffee...

MLOps.community ·

2022/10/21

MLOps Coffee Sessions #129 {Podcast BTS} with Catherin Breslin, Voice and Language Tech co-hosted by Adam Sroka. // Abstract Back in the day, Speech Recognition was its own thing. It's a very different flavor of Data Science. You could not use a lot of the tools. It wouldn't cross over to this type of machine learning. Now, with the advancements, Speech Recognition and Machine learning are coming in together. It's interesting to hear right from someone with a Ph.D. level working with some of the

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00:45:01

Managing Machine Learning Projects // Simon Thompson...

MLOps.community ·

2022/10/19

MLOps Coffee Sessions #128 with Simon Thompson, Managing Machine Learning Projects co-hosted by Abi Aryan. // Abstract It's a cliche to say that choosing and running the algorithms is only a small part of a typical ML project but despite that it's true! Setting up and organizing the project, dealing with the data asset, getting to the heart of the business problem, assessing and choosing the models, and integrating them with the business processes in production are all at least as time-consuming

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01:02:24

Reliable ML // Niall Murphy & Todd Underwood //...

MLOps.community ·

2022/10/07

MLOps Coffee Sessions #127 with Niall Murphy & Todd Underwood, Reliable ML co-hosted by David Aponte. // Abstract By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guest authors show you how to run an efficient and reliable ML system. Whether you want to increase revenue, optimize decision-making, solve problems, or understand and influence customer behavior, you'll

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00:51:00

ML Unicorn Start-up Investor Tells-IT-All // George...

MLOps.community ·

2022/10/04

MLOps Coffee Sessions #126 with George Mathew, ML Unicorn Start-up Investor Tells-IT-All. // Abstract What's so enticing about enterprise software? It's incredible to see George's idea and vision to invest in generationally enduring companies. Let's look at the way how George likes to structure deals with companies while he's reviewing them and let's look at the MLOps ecosystem through the eyes of the investors. // Bio George Mathew joins Insight Partners as a Managing Director focused on

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00:55:24

Databricks Model Serving V2 // Rafael Pierre //...

MLOps.community ·

2022/09/30

MLOps Coffee Sessions #125 with Rafael Pierre, Deploying Real-time ML Models in Minutes with Databricks Model Serving V2 co-hosted by Ryan Russon. // Abstract From our experience helping customers in the Data and AI field, we learned that the most challenging part of Machine Learning is deploying it. Putting models into production is complex and requires additional pieces of infrastructure as well as specialized people to take care of it - this is especially true if we are talking about real-time

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00:10:37

Monitoring Unstructured Data // Aparna Dhinakaran &...

MLOps.community ·

2022/09/27

Lightning Sessions #2 with Aparna Dhinakaran, Co-Founder and Chief Product Officer, and Jason Lopatecki, CEO and Co-Founder of Arize. Lightning Sessions is sponsored by Arize // Abstract Monitoring embeddings on unstructured data is not an easy feat let's be honest. Most of us know what it is but don't understand it one hundred percent. Thanks to Aparna and Jason of Arize for breaking down embedding so clearly. At the end of this Lightning talk, we get to see a demo of how Arize deals with

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00:58:47

Trustworthy Machine Learning // Kush Varshney //...

MLOps.community ·

2022/09/21

MLOps Coffee Sessions #124 with Kush Varshney, Distinguished Research Staff Member and Manager IBM Research, Trustworthy Machine Learning co-hosted by Krishnaram Kenthapadi. // Abstract Trustworthy ML is a way of thinking and something to be worked on and operationalized throughout the entire machine learning development lifecycle, starting from the problem specification phase that should include diverse stakeholders. // Bio Kush R. Varshney was born in Syracuse, New York in 1982. He received a

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00:52:08

RECOMMENDER SYSTEM: Why They Update Models 100 Times...

MLOps.community ·

2022/09/16

MLOps Coffee Sessions #123 with Gleb Abroskin, Machine Learning Engineer at Funcorp, RECOMMENDER SYSTEM: Why They Update Models 100 Times a Day co-hosted by Jake Noble. // Abstract FunCorp was a top 10 app store. It was a very popular app that has a ton of downloads and just memes. They need a recommendation system on top of that. Memes are super tricky because they're user-generated and they evolve very quickly. They're going to live and die by the Recommender System in that product. It's

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00:57:14

Scaling Similarity Learning at Digits // Hannes Hapke...

MLOps.community ·

2022/09/09

MLOps Coffee Sessions #122 with Hannes Hapke, Machine Learning Engineer at Digits Financial, Inc., Scaling Similarity Learning at Digits co-hosted by Vishnu Rachakonda. // Abstract Machine Learning in a product is a double-edged sword. It can make a product more useful but it depends on assumed and strictly defined behavior from users. Hannes walks through the entirety of their machine learning pipeline, how they implemented it, what the elements are, what the learning looks like, and what

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01:04:35

Bringing DevOps Agility to ML// Luis Ceze // Coffee...

MLOps.community ·

2022/09/06

MLOps Coffee Sessions #121 with Luis Ceze, CEO and Co-founder of OctoML, Bringing DevOps Agility to ML co-hosted by Mihail Eric. // Abstract There's something about this idea where people see a future where you don't need to think about infrastructure. You should just be able to do what you do and infrastructure happens. People understand that there is a lot of complexity underneath the hood and most data scientists or machine learning engineers start deploying things and shouldn't have to worry

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00:53:40

Feathr: LinkedIn's High-performance Feature Store //...

MLOps.community ·

2022/09/02

MLOps Coffee Sessions #120 with David Stein, Senior Staff Software Engineer at LinkedIn, Feathr: LinkedIn's Enterprise-Grade, High-Performance Feature Store co-hosted by Skylar Payne. // Abstract When David started building Feathr, Feature Stores did not exist. That was not a term floating around at all. This was definitely one of the OG Feature Stores for sure! We hear how the LinkedIn team got to this point, having an open source release, and how they used LinkedIn as an incubator to build a

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00:45:41

MLOps at DoorDash // Hien Luu and DoorDash Leads //...

MLOps.community ·

2022/08/30

MLOps Coffee Sessions #119 with Hien Luu, Sr. Engineering Manager of DoorDash, MLOps at DoorDash: 3 Principles for Building an ML Platform That Will Sustain Hypergrowth co-hosted by Skylar Payne. // Abstract Machine Learning plays a big part at DoorDash in terms of what they do on a daily basis. It powers many of their core infrastructures. When it comes to DoorDash's business, they have to be leveraging machine learning and it is such a huge piece of the business that it is critical. // Bio

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00:53:05

ML Platforms, Where to Start? // Olalekan Elesin //...

MLOps.community ·

2022/08/26

MLOps Coffee Sessions #118 with Olalekan Elesin, Director of Data Platform & Data Architect at HRS Product Solutions GmbH, co-hosted by Vishnu Rachkonda. // Abstract You don't have infinite resources? Call out your main metrics! Focus on the most impactful things that you could do for your data scientists. Olalekan joined us to talk about his experience previously building a machine learning platform at Scaleout24. From our standpoint, this is the best demonstration and explanation of the

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00:58:16

Data Engineering for ML // Chad Sanderson // Coffee...

MLOps.community ·

2022/08/19

MLOps Coffee Sessions #117 with Chad Sanderson, Head of Product, Data Platform at Convoy, Data Engineering for ML co-hosted by Josh Wills. // Abstract Data modeling is building relationships between core concepts within your data. The physical data model shows how the relationships manifest in your data environment but then there's the semantic data model, the way that entity relationship design is extracted away from any data-centric implementation. Let's do the good old fun of talking about

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00:54:02

Scaling Machine Learning with Data Mesh // Shawn...

MLOps.community ·

2022/08/17

MLOps Coffee Sessions #116 with Shawn Kyzer, Principal Data Engineer at Thoughtworks (Spain), Scaling Machine Learning with Data Mesh co-hosted by Adam Sroka. // Abstract You can't just get something done by using tools. You need to go much deeper than that and it is very clear that Data Mesh is the same thing. You have to educate the organization about the movement. In this session, Shawn broke down the cultural piece of data mesh and how many parallels there are with the MLOps Movement when it

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00:41:52

How Hera is an Enabler of MLOps Integrations //...

MLOps.community ·

2022/08/14

MLOps Coffee Sessions #115 with Flaviu Vadan, Senior Software Engineer at Dyno Therapeutics, How Hera is an Enabler of MLOps Integrations co-hosted by Vishnu Rachakonda. // Abstract Flaviu talks about the internal ML platform at Dyno Therapeutics called Hera. His team uses Hera as an internal innovation engine to help discover new breakthroughs with machine learning in the biotech healthcare industry. / Bio Flaviu is a Senior Software Engineer at Dyno Therapeutics, the leading organization in the

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514 results

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