Machine Learning, AI and Programming

How does Bitcoins work ?

When we do online transactions on our favorite e-commerce website, we pass the credit/debit card information to a payment gateway or the third party merchant (issuing the credit card) over a secure connection (HTTPS). The gateway or the merchant then validates this information and encrypts the transaction data and passes on to the issuing bank for clearance, after which the amount is credited to the seller account. One can quite obviously see that it is an […]

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The Future lies with Decentralization, or does it ?

Although Bitcoins and other Cryptocurrencies are hailed as the greatest revolution in financial technology, since it is a new although a revolutionary concept, financial and economic regulatory bodies worldwide are still skeptical about it (security issues, frauds, money laundering, criminal activity fundings etc.) and thus only a handful of merchants world over accept them. But the good news is that more people are starting to feel confident about it. It […]

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How cryptocurrency taught me a better concept of "money"

First of all let me admit that I do not have a formal economics or finance education and until sometimes back, like many others I used to think that money means the Rs. 100 or Rs. 500 currency note that we exchange with a business owner to purchase something of value to us. I did not think over why a paper note with some value printed on it could purchase me […]

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Expectation Maximization with an Example

In the last post, we introduced a technique called the Maximum Likelihood Estimation (MLE) to estimate unknown parameters of a probability distribution given a set of observations. Although it is a very useful technique, but it assumes that all information about the observation is available to us. Consider the example of a two coin toss : "Given two coins A and B, with probability of heads being 'p' and 'q' […]

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Maximum Likelihood Estimation

Observations from a probability distribution, depends on the parameters of that model. For example, given an unbiased coin with equal probability of landing heads as well as tails, what is probability of observing the sequence "HHTH". Our knowledge from probability theory says that since the toss of a coin follows the binomial distribution, the probability of the observation should be 0.54 = 0.0625, but what if the coin was biased and the […]

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