Data Scientists need skill and experience to create useful Machine Learning (ML) models. ML activities include tool selection, training logistic decisions (move data to training vs. train in-situ), data acquisition, data cleaning, data quality...
Good Vs. Evil - Two Opposing paths Taken by a Similar Genius This blog post provides a comparison between Henry David Thoreau's Walden and Ted Kaczynski's Unabomber Manifesto. To compare these two works, I use both a modern Natural Language...
I started my AI/ML journey in 2011 with a laptop model, a term which indicates a measure of size. Laptop models, by definition, do not exceed the compute, memory and storage resources of a single piece of hardware. The laptop model approach works...
Model optimization on traditional Artificial Intelligence and Machine Learning (AI/ML) platforms requires considerable Data Architect expertise and judgement. These ML platforms require the Architect to choose from dozens of available training...
FastAI provides Jupyter notebooks to wrangle data, train models, optimize models and then serve models. I recommended FastAI to my Data Scientist friends and they found the FastAI Jupyter layout and workflow both cumbersome and confusing. GCP...