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University of Cambridge > Talks.cam > Machine Learning Journal Club > Machine Learning Book Reading Club
Machine Learning Book Reading ClubAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Philipp Hennig. The Machine Learning book reading club is a new addition to the ML journal club series. It is aimed primarily at PhD students with an interest in the related fields of Machine Learning, Probability Theory, Neuroscience and Information Theory. Gaining a broad overview over one’s own and neighbouring fields is part of a PhD. Much of such knowledge can be gained from graduate text books, but it is often hard to sustain the motivation necessary to read through the whole of these often massive tomes. The ML book reading club can help to stay on track. Its goal is to read, at a comfortable, sustained pace, through a set of the standard text books. We meet once a week to discuss the contents of last week’s chapter(s). Currently, the long-term plan is to read through the following books
We will start off with the discussion of the “Introduction” chapter in Chris Bishop’s book (pp. 1 – 67). We will also use the first meeting to discuss good times for consecutive meetings and the general modus operandi. Over the summer, meetings will have to be in the early evening to accommodate those working outside of the University. This talk is part of the Machine Learning Journal Club series. This talk is included in these lists:
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