June 4, 2017
You might have heard of reinforcement learning, lots of its magical stories from media and are curious about what it is. Reinforcement learning is about getting an agent learn to act given rewards. RL is inspired by behavioral psychology. The process is just like teaching a pet: you don’t tell it what to do, but you reward/punish it when it does the right/wrong thing. There are plenty of online tutorials which give you comprehensive ideas about reinforcement learning.The ModelWe can describe ...
March 21, 2017
Topic modelling is a technique to automatically discover the hidden topics in each document. The basic idea is that words with similar meaning will occur in similar documents. A document is then modeled and described by topics coverages with word distributions. Latent Semantic Indexing (LSI) and Latent Dirichlet Allocation (LDA) are two common models. Practically the models perform similarly. Knowing a set of documents d1, …, dm and vocabulary words w1, …, wn, we can construct a document-term...
December 16, 2016
Word embeddings are dense vectors used to represent word meanings. Both Stanford’s GloVe and Google’s word2vec are open source packages and provide efficient implementations to train these vectors. Many pretrained vectors can be found online. I download the pretrained word vectors from the GloVe web. The vectors look like below, in each line a word is represented as a multidimentional vector of float values:pretrained = open("glove.6B/glove.6B.50d.txt", "r").readlines()for line in pretrained[...
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A data scientist, foodie,
♥ snowboarding and travelling.
