Interactive controls for Jupyter notebooks: Python Examples
19 Sep 2018 Examples on how to add interactive controls to jupyter notebooks.
Read More ›Caching Function Results in Python: Examples using Joblib and Functools
15 Sep 2018 In many cases (web development, data analysis, etc) it's useful to be able to store results that take long to re-compute. These solutions allow you to save results (either in memory or on disk) so that all function calls after the first one become constant-time lookups.
Read More ›Risk in Machine Learning Models
06 Sep 2018 Machine Learning models can make actual decisions that affect your business. However, things can go wrong, which introduces risk that must be dealt with.
Read More ›Paper Summary: SMOTE: Synthetic Minority Over-sampling Technique
01 Sep 2018 Summary of the 2002 article "SMOTE: Synthetic Minority Over-sampling Technique" by Chawla et al.
Heads-up for Deploying Scikit-learn Models to Production: Quick Checklist
01 Sep 2018 A couple of tips for addressing common problems and unexpected situations when using scikit-learn models in production..
Cross-Validation Examples with Scikit-Learn
01 Sep 2018 Using cross-validation within scikit-learn.
Read More ›Using SQL-like Syntax with Pandas Dataframe: Query and Eval Examples
05 Jul 2018 Use SQL-like syntax to perform in-place queries on pandas dataframes.
Read More ›paper-summary multi-label structured-learning hierarchical-learning natural-language-processing
Paper Summary: Multi-Label Classification on Tree- and DAG-Structured Hierarchies
02 Jul 2018 Summary of the 2011 article "Multi-Label Classification on Tree- and DAG-Structured Hierarchies" by Bi and Kwok.
Paper Summary: The Natural Language Decathlon
30 Jun 2018 Summary of the 2018 article "The Natural Language Decathlon" by McCann et al.
Example Project Template: Serve a Scikit-learn Model via a Flask API
27 Jun 2018 Full (albeit simple) example on how to create a simple Flask API to serve predictions using a pre-trained scikit-learn model. Includes supporting features such as logging, error handling, input validation, etc. Full code available on Github.