Lessons learned building a fish ID web app with fast.ai and Streamlit, in an attempt to reduce my fear of missing out on the latest deep learning developments.
Overview of a talk I gave at a deep learning course, focusing on AI ethics as the need for humans to think on the context and consequences of applying AI.
Is artificial/machine intelligence a future threat? I argue that it’s already here, with greedy robots already dominating our lives.
Causality is often overlooked but is of much higher relevance to most data scientists than deep learning.
Insights on data collection and machine learning from spending a month sailing, diving, and counting fish with Reef Life Survey.
Progress on my album cover classification project, highlighting lessons that would be useful to others who are getting started with deep learning.
To become proficient at solving data science problems, you need to get your hands dirty. Here, I used album cover classification to learn about deep learning.