Causal ML, Transparency & Time-Varying Treatments || Iyar Lin || Causal Bandits Ep. 008 (2024)

Send us Fan MailSupport the showVideo version available on YouTube Recorded on Sep 13, 2023 in Beit El'Azari, Israel The eternal dance between the data and the modelEarly in his career, Iyar realized that purely associative models cannot provide him with the answers to the questions he found most interesting. This realization laid the groundwork for his search for methods that go beyond statistical summaries of the data. What started as a lonely journey, led him to become a data science lead at his current company, where he fosters causal culture daily. Iyar developed a framework that helps digital product companies make better decisions regarding their products at scale and at budget. Here, causality is not just a concept, but a tool for change. Ready to dive in?------------------------------------------------------------------------------------------------------ About The GuestIyar Lin is a Data Science Lead at Loops, where he helps customers make better decisions leveraging causal inference and machine learning methods. He holds master's degree in statistics from The Hebrew University of Jerusalem. Before Loops, he worked at ViaSat and SimilarWeb. Connect with Iyar: - Iyar on LinkedIn- Iyar's web page About The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4). Connect with Alex: - Alex on the InternetLinksPapers - Breiman (2001) - Statistical Modeling: The Two CulturesBooks - Molak (2023) - Causal Inference and Discovery in Python- Pearl et al. (2016) - Causal InfereSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn:   https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io  The Causal Book: https://amzn.to/3QhsRz4