4 Reasons Why MongoDB Atlas is great for Machine Learning

4 Reasons Why MongoDB Atlas is great for Machine Learning

MongoDB is one of the best databases for machine learning for several reasons. The first reason is that MongoDB stores JSON documents and has a flexible schema

In the past, machine learning against relevant data required some heavy lifting. Most of the machine learning for something like “sentiment analytics” against social media tweets and posts required a new way of thinking about data. Traditional rows and columns in a relational database can store the text of a message but do not do so well with a thumbs up or thumbs down icon… or an emoji or a meme. As a human, we can easily look at the above images and we immediately know the sentiment for each image. For a computer, it’s not so easy. Suppose we are trying to learn how our products are perceived on social media. To start the process we pay for a massive dump of millions upon millions of relevant social media posts. Now we have to sort through all the data, match our specific products and we find there is a lot of icons and images. We have to store the data somewhere and then we have to process the images with machine learning to make sense of them. Next, we have to store the meaning of each image in a social media post back in a database of some sort to report how many of our customers feel a particular way about our products.

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How To Improve Data Quality When With Unsupervised Machine Learning

In this article, I describe how unsupervised ML can help in data preparation for machine learning projects and how it helps to get more accurate business insights.

How To Get Started With Machine Learning With The Right Mindset

You got intrigued by the machine learning world and wanted to get started as soon as possible, read all the articles, watched all the videos, but still isn’t sure about where to start, welcome to the club.