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 lifecycle. / Takeaways: - ...
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. //Oth...
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 favori...
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 charge of...
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 sense o...
Dec 20, 2020•54 min•Season 1Ep. 45
Coffee Sessions #22 with Carl Steinbach of LinkedIn, Deep in the Heart of Data. //Bio Carl is a Senior Staff Software Engineer and currently the Tech Lead for LinkedIn's Grid Development Team. He is a contributor to Emerging Architectures for Modern Data Infrastructure //Other links referenced by Carl: https://rise.cs.berkeley.edu/wp-content/uploads/2017/03/CIDR17.pdf https://www.youtube.com/watch?v=-xIai_FvcSk&ab_channel=WePayEngineering https://softwareengineeringdaily.com/2019/10/23/linke...
Dec 18, 2020•56 min•Season 1Ep. 22
ML and Encryption - It's all about secure insights #7! In this episode, we've invited Théo Ryffel, Founder of Arkhn and founding member of the Open-Mined community. // Abstract: In this episode, Théo introduces us to the concept of encrypted Machine Learning, when and the best practices to have it applied in the development of Machine Learning based solutions, and the challenges of building a community. //Other links to check on Théo: https://twitter.com/theoryffel https://arkhn.com https://open...
Dec 17, 2020•36 min•Season 1Ep. 7
**Privacy-preserving ML with Differential Privacy** Differential privacy is without a question one of the most innovative concepts that came around in the last decades, with a variety of different applications even when it comes to Machine Learning. Many are organizations already leveraging this technology to access and make sense of their most sensitive data, but what is it? How does it work? And how can we leverage it the most? To explain this and provide us a brief intro on Differential Priva...
Dec 14, 2020•36 min•Season 1Ep. 6
MLOps community meetup #44! Last Wednesday, we talked to Savin Goyal, Tech lead for the ML Infra team at Netflix. // Abstract: In this conversation, Savin talked about some of the challenges encountered and choices made by the Netflix ML Infrastructure team while developing tooling for data scientists. // Bio: Savin is an engineer on the ML Infrastructure team at Netflix. He focuses on building generalizable infrastructure to accelerate the impact of data science at Netflix. // Other links to ch...
Dec 14, 2020•56 min•Season 1Ep. 44
Coffee Sessions #21 with Benjamin Rogojan of Seattle Data Guy, A Conversation with Seattle Data Guy //Bio Ben has spent his career focused on all forms of data. He has focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. He has also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. Ben privately consults on data ...
Dec 08, 2020•47 min•Season 1Ep. 21
Coffee Sessions #20 with Neal Lathia of Monzo Bank, talking about Monzo Bank - An MLOps Case Study //Bio Neal is currently the Machine Learning Lead at Monzo in London, where his team focuses on building machine learning systems that optimise the app and help the company scale. Neal's work has always focused on applications that use machine learning - this has taken him from recommender systems to urban computing and travel information systems, digital health monitoring, smartphone sensors, and ...
Dec 07, 2020•1 hr 4 min•Season 1Ep. 20
** The intersection between DataOps and privacy** DataOps is considered by many as the new era of data management, a set of principles that emphasizes communication, collaboration, integration, and automation of cooperation between the different teams in an organization that have to deal with data: data engineers, data scientists to data analysts. But is there any relation between DataOps and data privacy protection? Can organizations leverage DataOps to ensure that their data is privacy complia...
Dec 03, 2020•33 min•Season 1Ep. 5
**Are Privacy Enhancing Technologies a myth** Data Privacy and machine learning are here to stay, and there’s no doubt they’re the hot trends to be following. But do they need to clash with each other? Can we have these titans to co-exist? It seems like finally 2020 and 2021 will be the years where Privacy Enhancing Technologies. But after all what are they? How are these techs being used and leveraged by organizations? Useful links: https://medium.com/@francis_49362/differential-privacy-not-a-c...
Nov 26, 2020•23 min•Season 1Ep. 4
Coffee Sessions #19 with Barr Moses of Monte Carlo, Introducing Data Downtime: How to Prevent Broken Data Pipelines with Observability co-hosted by Vishnu Rachakonda //Bio Barr Moses is CEO & Co-Founder of Monte Carlo, a data observability company backed by Accel and other top Silicon Valley investors. Previously, she was VP Customer Operations at customer success company Gainsight, where she helped scale the company 10x in revenue and among other functions, built the data/analytics team. Pr...
Nov 24, 2020•1 hr 1 min•Season 1Ep. 19
MLOps community meetup #43! Last Wednesday, we talked to Nathan Benaich, General Partner at Air Street Capital and Timothy Chen, Managing Partner at Essence VC about The MLOps Landscape. // Abstract: In this session, we explored the MLOps landscape through the eyes of two accomplished investors. Tim And Nathan shared with us their experience in looking at hundreds of ML and MLOps companies each year to highlight major insights they have gained. What do the ML infrastructure and tooling landscape...
Nov 23, 2020•59 min•Season 1Ep. 43
**AI and ethical dilemmas** Artificial Intelligence is seen by many as a vehicle for great transformation, but for others, it still remains a mystery, and many questions remain unanswered: will AI systems rule us one day? Can we trust AI to rule our criminal systems? Maybe create political campaigns and dominate political advertisements? Or maybe something less harmful, do our laundry? Some of these questions may sound absurd, but they are for sure making people shift from thinking purely about ...
Nov 19, 2020•52 min•Season 1Ep. 3
MLOps community meetup #42! Last Wednesday, we talked to Mark Craddock, Co-Founder & CTO, Global Certification and Training Ltd (GCATI), about UN Global Platform. // Abstract: Building a global big data platform for the UN. Streaming 600,000,000+ records / day into the platform. The strategy developed using Wardley Maps and the Platform Design Toolkit. // Bio: Mark contributed to the Cloud First policy for the UK Public sector and was one of the founding architects for the UK Governments G-C...
Nov 16, 2020•59 min•Season 1Ep. 43
What are regulations saying about data privacy? We are already aware of the importance of using Machine Learning to improve businesses, nevertheless to feed Machine Learning, data is a must, and in many cases, this data might even be considered sensitive information. So, does this mean that with new privacy regulations, access to data will be more and more difficult? ML and Data Science have their days counted? Or Will Machine beat privacy? To answer all these questions I’ve invited Cat Coode, a...
Nov 12, 2020•36 min•Season 1Ep. 2
In this episode, we talked to Elizabeth Chabot, Consultant at Deloitte, about When You Say Data Scientist Do You Mean Data Engineer? Lessons Learned From StartUp Life. // Key takeaways: If you have a data product that you want to function in production, you need MLOps Education needs to happen about the data product life cycle, noting that ML is just part of the equation Titles need to be defined to help outside users understand the differences in roles // Abstract: ML and AI may sound sexy to i...
Nov 10, 2020•1 hr 1 min•Season 1Ep. 42
MLOps community meetup #41! Last Wednesday was an exciting episode that some attendees couldn't help to ask when is the next season of their favorite series! The conversation was around Metaflow: Supercharging Data Scientist Productivity with none other than Netflix’s very own Ravi Kiran Chirravuri. // Abstract: Netflix's unique culture affords its data scientists an extraordinary amount of freedom. They are expected to build, deploy, and operate large machine learning workflows autonomously wit...
Nov 10, 2020•1 hr•Season 1Ep. 41
Coffee Sessions #18 with Luigi Patruno of ML in Production, a Centralized Repository of Best Practices Summary Luigi Patruno and ML in production MLOps workflow: Knowledge sharing and best practices Objective: learn! Links: ML in production: https://mlinproduction.com/ Why you start MLinProduction: https://mlinproduction.com/why-i-started-mlinproduction/ Luigi Patruno: a man whose goal is to help data scientists, ML engineers, and AI product managers, build and operate machine learning systems i...
Nov 09, 2020•47 min•Season 1Ep. 18
This is the first episode of a podcast series on Machine Learning and Data privacy. Machine Learning is the key to the new revolution in many industries. Nevertheless, ML does not exist without data and a lot of it, which in many cases results in the use of sensitive information. With new privacy regulations, access to data is today harder and much more difficult but, does that mean that ML and Data Science has its days counted? Will the Machines beat privacy? Don’t forget to subscribe to the ml...
Nov 05, 2020•19 min•Season 1Ep. 1
MLOps level 2: CI/CD pipeline automation For a rapid and reliable update of the pipelines in production, you need a robust automated CI/CD system. This automated CI/CD system lets your data scientists rapidly explore new ideas around feature engineering, model architecture, and hyperparameters. They can implement these ideas and automatically build, test, and deploy the new pipeline components to the target environment. Figure 4. CI/CD and automated ML pipeline. This MLOps setup includes the fol...
Nov 03, 2020•1 hr 1 min•Season 1Ep. 17
MLOps community meetup #40! Last Wednesday, we talked to Theofilos Papapanagiotou, Data Science Architect at Prosus, about Hands-on Serving Models Using KFserving. // Abstract: We looked to some popular model formats like the SavedModel of Tensorflow, the Model Archiver of PyTorch, pickle&ONNX, to understand how the weights of the NN are saved there, the graph, and the signature concepts. We discussed the relevant resources of the deployment stack of Istio (the Ingress gateway, the sidecar a...
Oct 30, 2020•58 min•Season 1Ep. 40
MLOps community meetup #39! Last week we talked to Ivan Nardini, Customer Engineer at SAS, about Operationalize Open Source Models with SAS Open Model Manager. // Abstract: Analytics are Open. According to their nature, Open Source technologies allows an agile development of the models, but it results difficult to put them in production. The goal of SAS is supporting customers in operationalize analytics In this meetup, I present SAS Open Model Manager, a containerized Modelops tool that acceler...
Oct 27, 2020•57 min•Season 1Ep. 38
//Bio Satish built compilers, profilers, IDEs, and other dev tools for over a decade. At Microsoft Research, he saw his colleagues solving hard program analysis problems using Machine Learning. That is when he got curious and started learning. His approach to ML is influenced by his software engineering background of building things for production. He has a keen interest in doing ML in production, which is a lot more than training and tuning the models. The first step is to understand the produc...
Oct 26, 2020•57 min•Season 1Ep. 16
James Sutton is an ML Engineer focused on helping enterprise bridge the gap between what they have now, and where they need to be to enable production scale ML deployments. ----------- 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 David on LinkedIn: https://www.lin...
Oct 20, 2020•1 hr 2 min•Season 1Ep. 15
