After PyData Warsaw 2017
A recap of PyData Warsaw 2017, covering key talks, new package announcements, and analytics on the conference's international attendees.
A recap of PyData Warsaw 2017, covering key talks, new package announcements, and analytics on the conference's international attendees.
Slides and resources from a talk on R programming and data science presented at the EARL Boston conference.
A curated collection of resources and tools for learning and using Regular Expressions (RegEx) in the R programming language.
A two-day workshop on survival analysis, covering data exploration, regression modeling, and practical sessions for time-to-event data.
A practical guide outlining essential tools, skills, and practice methods for beginners to start a career in data science.
Final part of a series on building a product classification API, covering the creation of a custom Python class and web app for categorizing product titles.
Announcing a public lecture series honoring statistician Ross Ihaka, featuring talks on statistical computing, data visualization, and data journalism.
A data scientist shares a technical interview task on linear regression, covering data cleaning, model fitting, and assumption validation.
A data scientist argues that data science and targeted advertising on social media have distorted reality and influenced major political events like Brexit and the US election.
Explores Bayesian vs. Frequentist approaches to the multiple comparisons problem in statistical inference and data analysis.
A curated list of five interesting Python tutorials covering music generation, computer vision, data science, and popular modules.
A guide for academics with math/physics backgrounds transitioning into data science, covering skills, learning paths, and practical advice.
A curated list of resources for beginners to learn Python specifically for data science, including tutorials, courses, and books.
A guide on creating a custom Docker container for R data science work, including installing packages and visualizing data.
A summary of a talk on achieving top 3% in a Kaggle competition, covering validation, feature engineering, and ensemble techniques.
Interview with data scientist Jeroen Janssens about his background, work on data science at the command line, and his Data Science Toolbox project.
Announcing EuroSciPy 2015, the European conference on Python for scientific computing, with calls for papers, talks, and tutorials.
Exploring the IBash Notebook, a Bash kernel for Jupyter, and its potential as a data science environment with inline image support.
A report on the 2014 scikit-learn developer sprint in Paris, covering participants, venues, achievements, and sponsors.
Explores how personas, data science, and k-means clustering can be used together to analyze user data and gain actionable business insights.