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Library Services

Machine learning & Artificial intelligence

A range of high-quality resources for Electronic Engineering and Computer Science are available on the web. For subject specific resources look at these guides:

Machine Learning

  • International conference on Machine Learning (ICML): Yearly conference. An archive of many seminars and talks from previous conferences is available.
  • Kaggle: Developed from a machine learning competition platform to be much more. Offers datasets and coding examples, and also free training opportunities.
  • Machine Learning - IBM: Provides a great introduction to machine learning and how a company like IBM is using it.
  • Machine Learning - an overview: Useful definitions and introductions of machine learning from academic texts delivered Science Direct.
  • Papers with code: Curated self-archived papers around primarily machine learning with the coding attached. 
  • Python Machine Learning: Freely available tutorials about machine learning in Python.
  • TensorFlow: A free open-sourced machine learning framework and platform, developed by Google Brain. The site offers access to an active developer community and tutorials to get started.
  • UCI Machine Learning Repository: Makes 622 data sets available to support the research around machine learning algorithms.

Artificial intelligence

  • Emerj: AI Research and Advisory company which offers other companies with best practice and use cases of AI in business. Some of these case studies are available freely on their website.
  • Deep learning Python language library. A free course is available for beginners.
  • Google AI: Learn about Google’s own research group around artificial intelligence.
  • IBM Developer - Artificial Intelligence: IBM's work around AI, gives access to datasets, open projects, blog, podcasts and other material.
  • KDnuggets: Blog, articles and free datasets and other useful links is made available.
  • OpenAI: Business concentrating on developing AI technology, and their website gives access to the code of some of their openai projects.

Queen Mary Research groups of interest

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