Li Maisi

Coupang is reimagining the shopping experience with the goal of wowing each customer from the instant they open the Coupang app to the moment an order is delivered to their door. The role of machine learning is becoming increasingly important in this innovation. Coupang's machine learning technology optimizes product search, pricing, inventory management, and logistics processing, and improves our customers' lives exponentially better. For more details, visit Coupang's Engineering Blog. ✅ Engineering Blog: https://lnkd.in/eRydERW5 #Coupang #CoupangCareers #CoupangTech #Tech #Engineer #DataEngineering

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🎙️ Invited Talk at San Diego State University on "𝐀 𝐂𝐨𝐦𝐩𝐚𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐨𝐟 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬" ➜ Talk: https://lnkd.in/gkz_ii_m ➜ Slides: https://lnkd.in/gWacgNCd ➜ Primer: http://ml-comp.aman.ai Thanks, Aaron Elkins, for hosting me. • Abstract: This talk provides a comparative analysis of core machine learning algorithms, with a focus on understanding their theoretical foundations, practical applications, and trade-offs. We begin with regression methods, exploring linear regression for modeling continuous outcomes, logistic regression for classification tasks, and locally weighted linear regression for handling non-linearity in data. Next, we examine Naïve Bayes classifiers, highlighting their probabilistic framework, scalability, and common use cases in text classification and spam detection. We then move to Support Vector Machines (SVMs), which offer robust solutions for high-dimensional data through margin maximization and kernel-based methods. Ensemble methods will be discussed in detail, emphasizing how techniques like bagging, boosting, and stacking combine weak learners to build more powerful predictive models. Decision trees, as the foundation of many ensemble methods, will also be analyzed for their interpretability and limitations. The talk will also cover unsupervised approaches, such as k-means clustering for partitioning unlabeled datasets and principal component analysis (PCA) for dimensionality reduction, which aid in uncovering hidden structure and improving efficiency in downstream tasks. We conclude by considering the comparative strengths, weaknesses, and use-case suitability of these algorithms, equipping practitioners with guidelines to choose the right approach for real-world machine learning problems. Further reading recommendations will be provided for those wishing to deepen their expertise in advanced methodologies. James Silberrad Brown Center for Artificial Intelligence #artificialintelligence #machinelearning

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Reflections on IT Recruitment in Japan: From 2024 to 2026 🇯🇵 I just remembered that I was interviewed regarding the IT industry in Japan and how recruitment works here back in 2024. I realized I never shared it on LinkedIn (better late than never!) Reading it back today, fascinating to see how much has stayed the same despite the AI boom. Two years ago, I spoke about: - The "Invisible" Market: Why local candidates often use job boards that hide their names and companies until they trust you, also data confidentiality. - The "Jiko Shoukai" Culture: The non-negotiable ritual of self-presentation in every interview round. - The Talent Gap: Why Japan physically cannot meet its IT needs (like the 400k+ engineer shortage) without global talent. While the technology has evolved, the core of Japan's recruitment remains Trust (Shinyo). Whether I'm placing an AI Engineer today or a Product Manager two years ago, the "Human" element is the only thing that hasn't been automated. You can read the full deep dive here (in Russian): 🔗 https://lnkd.in/gvjkAkhi If you are a company looking to enter the Japanese market or a candidate navigating these specific cultural waters, let's connect! The "rules" of the game are unique, but the rewards are worth it. #JapanTech #RecruitmentExpert #TokyoBusiness #ITRecruiter #CareerInsights #GlobalTalent #Networking

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