Hey folks! I am feeling really proud to announce the completion of my very own book. After a lot of hard-work and sheer determination this became possible and “Intermediate Python” saw the light of day. It will receive updates over time :) Continue reading
Hi there folks! I am very busy now-a-days. You might already be aware of that due to the long pauses between posts. Therefore, I am searching for guest bloggers who would like to write about Python, it’s frameworks or literally anything interesting and informative related to Python. Continue reading
Hi guys! I am in the USA right now. I am here to attend a Hackathon at the University of Michigan called MHacks 6. This is my first ever Hackathon so I am very excited. So now without wasting any time let’s get down to business. I recently came across a lot of nice tutorials which I believe might be useful for you guys. I am listing them below in no particular order: Continue reading
Originally posted on alexhwoods:
A Markov Chain is a random process, where we assume the previous state(s) hold sufficient predictive power in predicting the next state. Unlike flipping a coin, these events are dependent. It’s easier to understand through an example.
Imagine the weather can only be rainy or sunny. That is, the state space is rainy or sunny. We can represent our Markov model as a transition matrix, with each row being a state, and each column being the probability it moves to another.
In other words, given today is sunny, there is a .9 probability that tomorrow will be sunny, and a .1 probability that tomorrow will be rainy.
One cool application of this is a language model, in which we predict the next word based on the current word(s). If we just predict based on the last word…
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Hi guys. Recently my interview was published over at Mouse vs Python blog which is run by Mike. I am glad that I was able to become a part of Mike’s PyDev of the week series. This post is not going to be technical. I am going to use my time to clear up my mind through this post.