Workshop content:
Build your own drink classifier using image recognition! Are you Team Coffee or Team Boba Tea? By the end of this workshop, you’ll be able to classify photos using computer vision. The opportunities are endless.
Goals:
1. Introduce students to deep learning and computer vision through a hands-on project.
2. Build students' skills in using Jupyter Notebooks and fine-tuning pre-trained vision models.
3. Spark curiosity and interest in further learning about deep learning fundamentals.
Key Activities:
1. Introduction to deep learning, computer vision, and the workshop project.
2. Setting up the coding environment (Jupyter Notebooks, libraries).
3. Preparing the data (Bubble Tea and Coffee photo datasets).
4. Fine-tuning a pre-trained vision model for binary image classification.
5. Evaluating the model's performance on test data.
6. Visualizing and interpreting the activated feature detectors in the model's hidden layers.
7. Q&A and discussion on potential applications and further learning resources.
Workshop content:
Build your own drink classifier using image recognition! Are you Team Coffee or Team Boba Tea? By the end of this workshop, you’ll be able to classify photos using computer vision. The opportunities are endless.
Goals:
1. Introduce students to deep learning and computer vision through a hands-on project.
2. Build students' skills in using Jupyter Notebooks and fine-tuning pre-trained vision models.
3. Spark curiosity and interest in further learning about deep learning fundamentals.
Key Activities:
1. Introduction to deep learning, computer vision, and the workshop project.
2. Setting up the coding environment (Jupyter Notebooks, libraries).
3. Preparing the data (Bubble Tea and Coffee photo datasets).
4. Fine-tuning a pre-trained vision model for binary image classification.
5. Evaluating the model's performance on test data.
6. Visualizing and interpreting the activated feature detectors in the model's hidden layers.
7. Q&A and discussion on potential applications and further learning resources.
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