Data-Science
56 posts
Data Science Things Roundup #5
Explore Deep Q-Learning for Space Invaders, insights from Elasticsearch in production, and improved Python package management strategies.
Using survival analysis and git-pandas to estimate code quality
Apply survival analysis with git-pandas to measure code quality in Git repositories by analyzing code longevity and contributor patterns over time.
Git-pandas v1.0.0, or how to check for a stable release
Explore git-pandas v1.0.0, focusing on interface consistency, parameter naming, and API simplification for improved data analysis workflows.
Github.com cumulative blame in 5 lines of python
Visualize your GitHub repository growth over time using the git-pandas Python library and GitHubProfile class-all in just a few lines of code.
How to Write Comprehensions and Alienate People
A tongue-in-cheek guide to writing Python comprehensions that will make your colleagues question their life choices and your sanity.
Gitpandas v0.0.6: python 2.7, fileowners, file-wise blame and examples
Overview of git-pandas v0.0.6 release, highlighting new features like Python 2.7 support, file-wise blame, file owner determination, and other improvements.
Common Data Pitfalls for Recurring Machine Learning Systems
Explore common data pitfalls in recurring machine learning systems, including new categories, data format changes, sending issues, deduplication, and updates.
CyberLaunch: An Accelerator for Machine Learning Companies
Explore CyberLaunch, Atlanta's accelerator for machine learning and info security startups, its program details, and its impact on the local startup ecosystem.
Data Science Things Roundup #4
Data Science Things Roundup #4: Featuring Scikit-learn groups for feature sets, Markov Modulated Poisson Processes for event detection, and DBoost for boosting.
Beyond One-Hot: An Exploration of Categorical Variables
A deep dive into different methods for encoding categorical variables in machine learning, exploring their benefits and trade-offs