machine learning - elijah tai

[long-form] What’s your dataset worth?

Aswath Damodaran is a Professor of Finance at the Stern School of Business at NYU. He lectures on corporate finance and equity valuation, and maintains a blog called Musings on Markets, where he's shared and continues to share a vast wealth of knowledge on

data science

[note] Tutorial on Maximum Likelihood Estimation

http://times.cs.uiuc.edu/course/410/note/mle.pdfSearching across a space of models Structure and inner working of processes of interest are given by models, or "parametric families of probability distributions" Once you get a model want to know how well it

data science

[note] Tensorflow Tutorial: Vector Representations of Words

word2vec comes in two flavours: the Continuous Bag-of-Words (CBOW) model predicts target words (e.g. ‘mat’) from source context words (‘the cat sits on the’) smooths over much of the distributional information by treating entire context as one observation (better for smaller datasets) the

synthetic biology

[links] Synthetic biology and artificial intelligence

Artificial intelligence and synthetic biology: a tri-temporal contribution http://sci-hub.cc/10.1016/j.biosystems.2016.01.001 What can synthetic biology offer to artificial intelligence (and vice versa)? http://sci-hub.cc/10.1016/j.biosystems.2016.09.005 * cybernetics * autopoietic biology Synthetic biology

privacy

[note] On the Protection of Private Information in Machine Learning Systems: Two Recent Approaches

Mart´ın Abadi, Ulfar Erlingsson, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Nicolas Papernot∗, Kunal Talwar, and Li Zhang What’s the paper about:A look at some of the older ideas in privacy and how they can help with keeping private the training