Announcing a public lecture series honoring statistician Ross Ihaka, featuring talks on statistical computing, data visualization, and data journalism.
A guide to building a custom data science workstation for GPU computing and Docker, including specs, assembly, and a later upgrade.
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.
Guide on using R within Jupyter Notebooks to analyze and manipulate datasets in Oracle Big Data Discovery, enabling advanced statistical workflows.
Analysis of 21 million England and Wales house price records using data science techniques like Gini coefficient and inflation adjustment.
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.
A guide for Python/R users transitioning to Java, focusing on the necessity of IDEs like Eclipse or IntelliJ for productive development.
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.
Author's 2014 review: writing a data science book from scratch in Python and preparing for/starting a software engineering job at Google.
A review of the book 'Data Science at the Command Line', highlighting its approach to data manipulation and analysis using command-line tools.
An interactive exploration using IPython to simulate and understand the mathematical model behind 'The Hipster Effect' paper on conformity and non-conformity.
A response to a critique of the author's introductory series on Frequentist vs. Bayesian statistics, focusing on audience and the role of decision theory.
