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This post is the third part of the multi-part series on how to build a search engine –
Added by Vivek Kalyanarangan on December 30, 2016 at 6:00am — No Comments
Most analytic people would agree that lottery is a tax on the innumerate. However, for this statement to be true, we need to assume that winning numbers (and any combination of digits from these numbers) are truly random. If not, of course smart people are going to find and devise algorithms to increase their odds of winning, and/or will try to sell their magic "winning numbers" to idiots. …Continue
This post is the second part of the multi-part series on how to build a search engine –
Added by Vivek Kalyanarangan on December 23, 2016 at 10:30am — No Comments
Most tasks in Machine Learning can be reduced to classification tasks. For example, we have a medical dataset and we want to classify who has diabetes (positive class) and who doesn’t (negative class). We have a dataset from the financial world and want to know which customers will default on their credit (positive class) and which customers will not (negative class).
To do this, we can train a Classifier with a ‘training dataset’ and after such a Classifier is…
Added by ahmet taspinar on December 22, 2016 at 10:30am — No Comments
In this multi-part series, we will explore how to build a search engine. It will be quite powerful and industrial strength. The first part will focus on getting the right tools and getting technology stack ready. We will build this search engine with an AngularJS front-end and use elasticsearch as the computation back end.
This post is the first part of the multi-part series on how to build a search engine –
Added by Vivek Kalyanarangan on December 16, 2016 at 2:00am — No Comments
Deep learning is all the rage. You hear about it in the news, you read it about it in the news and it’s all over popular culture as well. What’s more, it’s revolutionizing the tech industry, as computers…Continue
Added by Malia Keirsey on December 5, 2016 at 12:00pm — No Comments