This episode shares how the applied science team developed an ad simulation system as a more efficient and economical evaluation method for the Uber Eats Ads business. This tool has proven instrumental in guiding and expediting product development and driving growth.

Based on the tech blog from Uber, the link is provided here for your reference: https://www.uber.com/blog/unleashing-the-power-of-ads-simulation/

This episode shares how the HelloFresh data science team explores the use of generative AI to create new food recipes.

Based on the tech blog shared by Data Scientist from HelloFresh, the blog link is: https://medium.com/hellofresh-dev/recipes-and-generative-ai-6d74a107860c

This podcast episode delves into my journey of utilizing unconventional learning methods to fulfill my 2023 New Year's resolution of enhancing my chess skills. The high-level concept and philosophy apply to Learning in general and it aims to inspire others to reflect on their best learning strategies on various topics, such as Data Science and Machine Learning.

This episode includes a re-distribution of the interview I had with Daliana Liu on her podcast "The Data Scientist Show" (https://open.spotify.com/episode/0HzWSLIWpz6iHJiKXs0GNJ)

There, I shared my thoughts about the focus difference between machine learning engineering and product data science, some projects I worked on at Uber and LinkedIn, as well as other topics: such as why I transitioned from an individual contributor into a manager; and the cultures I experienced in different tech companies.

This episode discusses one company's journey to enable product personalization, starting with customer cohort based recommendation to user-level personalized experience using Learning to Rank algorithm.

Based on the tech blog shared by Data Scientists from CARS24, the blog link is: ⁠⁠https://medium.com/cars24-data-science-blog/personalized-buyer-listings-at-cars24-an-overview-83d8428bd7d9

This episode discusses how to leverage the marketing mix model (MMM) to better understand and optimize company's marketing strategies.

Based on the tech blog shared by Data Scientist from Haleon, the blog link is: ⁠https://medium.com/trusted-data-science-haleon/optimising-marketing-allocation-with-marketing-mix-models-382c9e471dde

This episode discusses how the team develops a Generative AI solution to create engaging email subject lines by combining a reward model and prompt engineering over ChatGPT APIs.

Based on the tech blog shared by Machine Learning Engineers from Nextdoor, the blog link is: https://engblog.nextdoor.com/let-ai-entertain-you-increasing-user-engagement-with-generative-ai-and-rejection-sampling-50a402264f56

This episode discusses what is customer segmentation and how to use the k-means clustering algorithm over Recency, Frequency, and Monetary (RFM) segmentation features to generate them algorithmically.

Based on the tech blog shared by a Data Scientist from Microsoft, the blog link is: https://medium.com/data-science-at-microsoft/introduction-to-clustering-based-customer-segmentation-2fac61e80100

This episode discusses how contrastive learning (one self-supervised machine learning algorithm) is used to enable in-video search capability, and help facilitate creating promotional videos.

Based on the tech blog shared by Machine Learning Engineers from Netflix, the blog link is: https://netflixtechblog.com/building-in-video-search-936766f0017c

This episode discusses what is geo experimentation, and how synthetic control methods can be used to help make it more efficient, along with some tips and good practices shared by the blogpost author.

Based on the tech blog shared by Data Scientists from Mercado Libre, the blog link is: ⁠⁠⁠⁠⁠⁠⁠https://medium.com/mercadolibre-tech/harnessing-the-power-of-geo-experimentation-how-mercado-libre-measures-the-effectiveness-of-its-f68b38857c4b