Working as Data Scientists, we have to solve various problems on a daily basis. Some of them are tasks we've completed many times before and some of them are completely new to us and we have to understand the business logic behind them before starting building models. The latter was the case when our client, a bank, approached us a couple of months ago with a problem they were tackling – whether to provide or deny loans to gamblers.
In this post we will show you how to scrape reviews from an amazon product page. This data can be used to create datasets for sentiment analysis or other educational or research purposes. If you sell products on Amazon it can even be useful to analyse the reviews to understand what customers like and dislike about your product. Let's dive in!
Considering all the craze around cryptocurrencies happening all around us this year, our team has also decided to dip their toes into these crypto-waters and invest a little bit of money into the hype. In this blog, we will build a simple Google Sheet based portfolio monitoring tool. It is supposed to auto-update with new values on exchange rate changes.
In this post we will use modern Natural Language Processing techniques to find similar posts in a Facebook group.You have probably been in a situation where you want to post something in a Facebook group but you are not sure whether almost the same post already exists and is maybe just hiding on the next page.
Gut feeling used to be the biggest asset of successful businessmen in the past. Nowadays, intuition still plays an important role, but with all the available knowledge and technologies, there has been a significant shift. One of the most important sources of a competitive advantage these days is data. Big Data is a hype and undoubtedly a bandwagon to jump on. But how?