WeAreDevelopers LIVE • Dec 16, 2024

Mastering Image Classification: A Journey with Cakes

Carly Richmonds

Carly Richmond proves standard web developers can conquer machine learning without deep math. Learn to build custom image classifiers using TensorFlow.js and transfer learning to detect hyper-realistic cakes.

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#1 about 5 min

Introduction to image classification and the cake detection challenge

The premise of the presentation and the popular game show that inspired analyzing object classification.

#2 about 3 min

Sourcing and preparing custom images for a binary dataset

Scraping web images with Playwright and managing a dataset of cakes versus non-cakes to prepare for training.

#3 about 6 min

Evaluating MobileNet and COCO-SSD pre-trained computer vision models

Using out-of-the-box TensorFlow.js model algorithms for general classification and specific object detection on custom images.

#4 about 7 min

Building a custom Convolutional Neural Network pipeline from scratch

Creating, compiling, and training a sequential convolutional neural network in TensorFlow.js to isolate image features.

#5 about 3 min

Improving detection accuracy by reusing features through transfer learning

Combining MobileNet feature extraction with a custom classification head to bypass initial training failures.

#6 about 4 min

Testing human visual accuracy against multiple machine learning models

An interactive demonstration comparing human visual detection against various evaluated computer vision programs to measure accuracy.

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