Why Data Science Follows the Research Model, Not the Software Development Model
Software development succeeds 4 out of 5 times. Data science succeeds 1 out of 5. That difference is not a quality problem — it is a fundamental difference in the nature of the work. DS follows the academic research model: hypothesis, experiment, documented failure, iterate.
Five Stages of a Successful Cloud Data Science Platform
The standard SDLC model breaks for data science because model training requires production data. Here is a five-stage promotion framework that resolves the conflict between data scientist flexibility and production security controls.
ASR with PyTorch
Exploring whether modern PyTorch ASR pipelines expose phoneme-level representations, using Wav2Vec 2.0 to extract and visualize phoneme probabilities from speech.
A long time between posts
Resurrecting a technical blog after seven years away — migrating old WordPress archives, Google Blogger posts, and 1990s DarkMagic.org content into a new Jekyll site on GitHub Pages.