This session will be a practical introduction to machine learning and AI for charities. Through real-world examples and case studies, attendees will learn the fundamental concepts of ML/AI in plain language, gaining an understanding of how these technologies differ from other approaches. The session will explore three core ML techniques: classification, regression, and clustering. We'll examine both successful implementations and examples where ML doesn't work as expected, helping you understand when and how to apply these tools effectively.
このコースでは次の内容を学べます:
Explain what machine learning and AI are in accessible, non-technical language
Distinguish between the three main types of ML approaches: classification, regression, and clustering
Identify potential ML/AI applications relevant to their organisation's work
Eleanor is a Senior Data Scientist at Datarock and a Fellow at the Good Data Institute. Her career began with a PhD and postdoctoral research in experimental geochemistry, which involved making rocks in the lab and zapping them with electrons and lasers. She was drawn out of academia after seeing the potential of data science to make an immediate impact in a variety of sectors, from mining to non-profits.
Vivek Katial
Co-Founder and Executive Director
Good Data Institute
🎗💫 Executive Director at the Good Data
Institute -- connecting charities to a community of socially-minded data
professionals
📊👷♂️ Founding team & Data Scientist at
Multitudes, we're on a mission to make equity the default at work. Check
us out multitudes.co
⚛️🔬 PhD in Quantum Computing at the University of Melbourne — Instance Space Analysis of Variational Quantum Algorithms
I
am someone who loves math, coding and travel. I pride myself on making
my work reproducible and thrive for best practice. I enjoy getting my
hands dirty in data and am always looking for opportunities where
technology can be used for social good.