Coffee With Developers Mar 5, 2025

Building Your Own Classification Model with JavaScript - Coffee with Developers - Carly Richmond

Carly Richmnd

Carly Richmond warns that off-the-shelf AI plugins stifle developer curiosity. Discover how she built a TensorFlow.js classification model to prove the lasting value of hands-on tinkering.

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#1 about 3 min

Experimenting with JavaScript machine learning for cake detection

Building an image classification game using TensorFlow to identify objects disguised as cakes.

#2 about 5 min

Comparing custom machine learning models with transfer classification

How using pre-trained models like MobileNet improves accuracy over building custom binary classifiers from scratch.

#3 about 4 min

Impact of prebuilt artificial intelligence on developer curiosity

Relying on pre-built AI models out of convenience reduces learning opportunities for software engineers.

#4 about 4 min

Carving out dedicated time for engineering side projects

How engineering leaders can intentionally schedule gap days to retain coding skills and technical depth.

#5 about 5 min

Maintaining the value of hackathons and unstructured exploration

Management buy-in and clear outcomes are necessary to prevent developers from abandoning internal hack days.

#6 about 4 min

Evaluating trust and transparency in machine learning models

Why standardized model cards are crucial for understanding the dataset limitations and biases of pre-trained models.

#7 about 4 min

How dominant language models change developer search behavior

The affordability barrier of custom datasets pushes engineers toward off-the-shelf artificial intelligence tools without validating responses.

#8 about 5 min

Preserving authenticity in technical content and documentation writing

Why the surge of automated content generation shifts the engineering role toward fact-checking and reviewing code.

#9 about 6 min

Balancing artificial intelligence automation with human connection and ethics

The importance of establishing ethical usage policies to combat deep fakes and preserve human storytelling.

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