What is Big Data in Machine Learning? Definition & Algorithms

Big data is used to describe a dataset that, due to its value, variety, volume, and velocity, defies conventional methods of processing and would be impossible for a human to process without the assistance of an advanced machine. Big data does not have an exact definition in terms of size or the total number of rows and columns. 

Big Data Definition @pexels

At the moment, petabytes qualify as big data, but datasets are becoming increasingly larger as we find new ways to efficiently collect and store data at low cost. And with big data also comes greater noise and complicated data structures. A huge part, therefore, of working with big data is scrubbing: the process of refining your dataset before building your model.

After scrubbing the dataset, the next step is to pull out your machine learning equipment. In terms of tools, there are no real surprises. Advanced learners are still using the same machine learning libraries, programming languages, and programming environments as beginners. 

However, given that advanced learners are now dealing with up to petabytes of data, robust infrastructure is required. Instead of relying on the CPU of a personal computer, advanced students typically turn to distributed computing and a cloud provider such as Amazon Web Services (AWS) to run their data processing on what is known as a Graphical Processing Unit (GPU) instance.

GPU chips were originally added to PC motherboards and video consoles such as the PlayStation 2 and the Xbox for gaming purposes. They were developed to accelerate the creation of images with millions of pixels whose frames needed to be constantly recalculated to display output in less than a second. 

By 2005, GPU chips were produced in such large quantities that their price had dropped dramatically and they’d essentially matured into a commodity. Although highly popular in the video game industry, the application of such computer chips in the space of machine learning was not fully understood or realized until recently.