An analysis and English translation of Jacek Kaczmarski's poem 'The Statues', exploring the legacy of tyranny.
The article critiques the overuse and devaluation of the titles 'Engineer' and 'Scientist' in modern IT, focusing on data science and engineering roles.
A case study on building and deploying a machine learning system for hospital bill estimation, reducing prediction errors by over 50%.
A critique of the Oxford-Munich Code of Conduct for Data Scientists, focusing on its technical recommendations on sampling and data retention.
An exploration of predictive analytics, its historical roots in human nature, and its modern implementation through data science and AI technologies.
Explains the theory behind linear regression models, a fundamental machine learning algorithm for predicting continuous numerical values.
A guide to setting up a GPU-powered JupyterHub environment on AWS for a data science hackathon, including driver installation and configuration.
A crash course on the theory behind linear regression models, a fundamental machine learning algorithm for predicting numerical values.
A review and tips for the OMSCS CS7646 Machine Learning for Trading course, covering the author's experience and key takeaways.
A case study on building a production ML system to predict patient hospitalization costs for Southeast Asia's largest healthcare group.
Announcement for a lecture series on machine learning, covering topics like Weka, deep learning, algorithmic fairness, and sparse supervised learning.
A researcher's 2018 highlights: using machine learning for cognitive brain mapping, analyzing non-curated data, and contributing to scikit-learn development.
A guide on building a personal brand as a data scientist, covering path selection, blogging, and sharing knowledge within the community.
Explains four levels of customer targeting, from no segmentation to advanced recommendation systems, and their business applications.
A critique of traditional statistics education, arguing for a more data-driven, question-focused approach using modern tools.
A data scientist shares ideas for micro-projects for the Summer of Data Science, including manual annotation, package comparisons, and resource curation.
A data scientist explains why he's attending the eRum 2018 R conference in Budapest instead of useR! this year, and provides details about the event.
A tutorial on using Daskernetes to create auto-scaling, personal Python clusters on Kubernetes for distributed computing tasks.
A summary of a Python Frederick meetup featuring Christine Lee's presentation on data science tools and features available in Python.
A curated list of resources and tutorials for using Docker with R to create reproducible research environments and containerized applications.
