Here are a selection of machine learning, AI and NLP resources you may find helpful.
Getting Started with AI and ML
I wrote some articles about the machine learning development cycle and how you should train and test models back when I worked at IBM.
- Cognitive Quality Assurance - An Introduction
- Cognitive Quality Assurance pt. 2 - Performance Metrics
Essays and FAQs
An assortment of essays and articles on philosophical concepts and frequently-asked-questions around AI concepts:
- GPUS are not just for images any more… explains why GPUs are important for machine learning and what their limitations are.
- Re-using machine learning models and the ‘no free lunch’ theorem explains how reusing machine learning models can be useful but also talks about where it doesn’t work.
- AI Can’t solve all our problems but that doesn’t mean it isn’t intelligent deals with the hype bubble around AI and deep learning in recent years.
Other people’s stuff
- If you’re interested in NLP I’d certainly suggest subscribing to Sebastian Ruder’s NLP Newsletter which provides highlights about state-of-the-art NLP stuff.
- colah’s blog provides lots of good explanations for some fairly complex neural models
- Joseph Misiti’s awesome machine learning repository provides a curated set of ML resources in a github repository.