A data scientist describes a simple yet effective custom embedding technique for image defect detection, outperforming a complex deep learning model on the KolektorSDD2 dataset.
A theoretical introduction to Linear Regression models, explaining their use for predicting continuous variables and importance in interpretable fields like lending.
A guide on tailoring your resume for different machine learning roles like Data Scientist and ML Engineer, using a 3-step process.
A podcast interview discussing reinforcement learning applications, data science career paths, and productivity insights for tech professionals.
Announcing the 2022 Ihaka Lectures, featuring online talks by Emi Tanaka, Luke Tierney, and Wes McKinney on R, data science tools, and experimental design.
Part 2 of a series on using Azure Anomaly Detector to identify unusual patterns in air quality sensor data for safety alerts.
A data scientist shares a structured approach to starting data science projects, focusing on business goals, requirements, and avoiding common pitfalls.
A data leader shares advice on creating a vision and roadmap for a data team, including stakeholder engagement and problem evaluation.
A data scientist shares lessons from writing online, focusing on learning, sharing ideas, and overcoming self-doubt as a non-writer in tech.
Scikit-learn foundation seeks a community and partnerships developer to grow the open-source ecosystem and foster industry sponsorships.
Profile of Amazon applied scientist Eugene Yan, focusing on his career in data science and his influential technical writing about machine learning.
A data scientist shares practical strategies and mindsets for influencing technical teams and driving change without formal authority.
Explores the distinction between using regression models for causal inference versus predictive inference, and the role of generalizability in prediction.
Explores the strategic 'metagame' of applying machine learning in industry, focusing on problem selection and business impact over pure technical knowledge.
A guest post sharing personal stories of imposter syndrome in tech and academia, with lessons on recognizing and managing self-doubt.
A data science leader shares insights from a fireside chat on building and running data teams, focusing on their role as profit centers and collaboration strategies.
A podcast episode exploring life lessons derived from machine learning concepts like data cleaning, explore-exploit, and overfitting.
A technical guide on how to include and organize non-blogpost content like slides and reports within a Distill blog built with RMarkdown.
A data scientist explains the 'Why, What, How' framework for writing effective technical documents like one-pagers, design docs, and after-action reviews.
A technical tutorial on using R and geospatial analysis to find areas with similar topography to a query region, focusing on spatial pattern matching.
