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From 1 to 100+ ML Models in Four Years
Architectural Patterns in ML
Building Agility and Velocity In Machine Learning From The Ground Up
Key Factors When Building a Global Data Science Team
TWIMLcon Day 6
Moving Faster with Data Science and Machine Learning Platforms

Recent Posts

Solmaz Shahalizadeh Blog post 1 to 100 models in four years at Shopify
In our recent TWIMLcon conversation with Solmaz Shahalizadeh, VP of Commerce Intelligence at Shopify, she shared her journey from deploying Shopify’s first machine learning model four years ago to now having over 100 models in production across all aspects of the business. Though she had much to share, one quote that stood out was, “If...
Nishan Subedi, VP of Algorithms at Overstock.com, Architerctural Patterns in ML
In our recent conversation with Nishan Subedi, VP of Algorithms at Overstock.com, he shared with us his approach to machine learning systems and organizational design. Applying architectural patterns to ML system design Nishan shared how the seminal book “Design Patterns: Elements of Reusable Object-Oriented Software” inspired him to look at system architecture as a set...
Building Agility and Velocity In Machine Learning From The Ground Up with Chris Albon, Director of Machine Learning, Wikimedia
How do you build a machine learning platform for one of the world’s largest websites from the ground up? This is the question we posed to Chris Albon, Director of Machine Learning, at the Wikimedia Foundation. This is what told us: Learn everything you can about your organization, the customers it serves, and the critical...
Key Factors When Building A Global Data Science Team: Insights from Our Interview with Ya Xu, Head of Data Science at LinkedIn
What are the most important factors to consider when building a global data science team? Ya Xu, Head of Data Science at LinkedIn, recently shared at TWIMLcon how she went from being an individual contributor to becoming a data science leader with over 350 global team members. During our conversation, Ya encouraged us to remember...
TWIMLcon Day 6<br/>Moving Faster with Data Science and Machine Learning Platforms
Today was the sixth day of TWIMLcon and the final day of presentations before we head into a full day of workshops and then a wrap-up unconference. Today we were fortunate to speak to folks from LinkedIn, Intuit, Cloudera, Yelp, Rakuten, Microsoft, Salesforce, and Fiddler. We covered a variety of subjects including: how to build...
TWIMLcon Day 5:<br/>Architecting ML Systems for Inevitable Change
What a start to week two of TWIMLcon 2021! Today’s sessions featured speakers from WikiMedia, Prosus Group, Palo Alto Networks, Clorox, Dataiku, Janssen Pharmaceutical Companies, iRobot, Algorithmia, and ClearML sharing their thoughts on building and running data science and ML platforms. We also got an overview of major themes and trends in machine learning for...
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