Eugene Yan is a Principal Applied Scientist at Amazon, building AI-powered recommendation systems and experiences. He shares insights on RecSys, LLMs, and applied machine learning, while mentoring and investing in ML startups.
185 articles from this blog
A guide on preparing and delivering effective data science presentations, covering motivation, topic selection, and storytelling techniques.
A metaphor using commandos, soldiers, and police to describe different career roles in tech startups and projects, focusing on risk and work style.
Explains why traditional note-taking fails and introduces the Zettelkasten method for connecting ideas to boost learning and productivity.
A guide to streamlining ML experiments by combining Jupyter, Papermill, and MLflow for parameterized runs and centralized logging.
A psychology graduate shares his unconventional journey into data science, detailing his career transition and lessons learned to help others.
A summary of a meetup talk on advanced recommender systems, exploring techniques beyond baselines using graph and NLP methods.
Explores improving recommender systems using graph-based methods and NLP techniques like word2vec and DeepWalk in PyTorch.
A guide to building a recommender system using PyTorch on a laptop, covering data acquisition, parsing, and multiple modeling techniques.
A graduate's review of the challenging CS6200 Introduction to Operating Systems course in the OMSCS program, covering projects, workload, and tips.
A case study on building and deploying a machine learning system for hospital bill estimation, reducing prediction errors by over 50%.
A keynote presentation on scaling tech platforms and the SuperApp strategy, using case studies from Alibaba, Grab, and WeChat.
A review and tips for the OMSCS CS6750 Human-Computer Interaction course, covering its structure, workload, and value for tech professionals.
Author migrates blog from Wordpress to Jekyll, highlighting new features like LaTeX support, collapsibles, and syntax highlighting.
A review of the OMSCS CS6440 Intro to Health Informatics course, covering content, workload, and tips for success.
A review and tips for the OMSCS CS7646 Machine Learning for Trading course, covering the author's experience and key takeaways.
A data scientist clarifies common misconceptions about the field, explaining that machine learning is only a small part of the job and advanced degrees aren't always required.
A case study on building a production ML system to predict patient hospitalization costs for Southeast Asia's largest healthcare group.
Explores adapting Agile/Scrum frameworks for data science teams, covering effective practices and necessary adjustments for the unique challenges of data science work.
Analyzes how Agile methodologies like Scrum can be applied to data science teams, highlighting effective practices and inherent challenges.
A summary of a panel discussion on various data roles (data scientist, ML engineer, etc.), including key skills and career insights.
