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 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.
Announcing the 2021 Ihaka Lectures featuring local experts on distributed computing, machine learning for child welfare, and applied math for COVID-19 response.
Explains the theory behind linear regression models, a fundamental machine learning algorithm for predicting continuous numerical values.
A podcast transcript discussing the importance of writing for career growth in tech, covering motivation, process, and Amazon's writing culture.
A data scientist's 2020 review, focusing on machine learning projects for healthcare, including mining COVID-19 EHR data and brain signal analysis.
A data visualization designer reflects on their 2020 freelance work, challenge contributions, and personal projects using R, ggplot2, and plotly.
A data scientist's 2020 reflection on moving to Amazon, building ML systems, and establishing a weekly writing habit for learning and sharing knowledge.
An interview with lead data scientist Alexey Grigorev on his career transition from software engineering to data science, his advice, and his work at OLX.
Explains the differences between Applied Scientist, Research Scientist, and ML Engineer roles in data science and machine learning.
