David Martin

Practical insights for a data-driven approach to model optimization David Martin · Follow Published in Towards Data Science · 7 min read · 4 days ago — Photo by Hal Gatewood on Unsplash In this last part of my series, I will share what I have learned on selecting a model for image classification and how to fine tune that model. I will also show how you can leverage the model to accelerate your labelling

Practical insights for a data-driven approach to model optimization David Martin · Follow Published in Towards Data Science · 11 min read · 4 days ago — Photo by FlyD on Unsplash In this third part of my series, I will explore the evaluation process which is a critical piece that will lead to a cleaner data set and elevate your model performance. We will see the difference between evaluation of a trained model (one

Practical insights for a data-driven approach to model optimization David Martin · Follow Published in Towards Data Science · 8 min read · 4 days ago — Photo by Conny Schneider on Unsplash In Part 1, we discussed the importance of collecting good image data and assigning proper labels for your image classification project to be successful. Also, we talked about classes and sub-classes of your data. These may seem pretty straight forward concepts, but

Practical insights for a data-driven approach to model optimization David Martin · Follow Published in Towards Data Science · 11 min read · 3 days ago — Photo by Joshua Sortino on Unsplash It is said that in order for a machine learning model to be successful, you need to have good data. While this is true (and pretty much obvious), it is extremely difficult to define, build, and sustain good data. Let me share