Data comes in many shapes and sizes. Every type of data poses a new problem for data scientists and analysts. Who have to figure out the best way to gather and clean. It before it gets analyzed.
Structured Vs. Unstructured data
Now, imagine if we were to ask for the job function email list database of each scientist. Ellen would send a spreadsheet file over the internet, while Charlie would literally show up one day with a folder filled with pieces of paper with different values and dates written all over the place.
Ellen’s database is an example of structured data. It’s data that has a model, or that follows a clear pattern that one could discern. Charlie’s is an example of unstructured data. Assuming that he didn’t make any mistakes, his data is as equally valuable as Ellen’s, but it’s more difficult to organize and process.
Data analysis with the help of AI
The growth of AI technology in the last the way to greatness couple of decades has opened the floodgate of new and better strategies for dealing with data. Thanks to machine learning and intelligent assistants we can gather, clean, and process unimaginable amounts of data in record time.
For example, streaming services use machine learning to find correlations in consumption habits so they can build a recommendation pool for people with similar tastes. Another example is how web stores will try to guess what you are likely to buy based on your purchasing and browsing history.
Learning in this context means that the algorithm gets better the more data it processes. Think of it as a tool that gets more sharp and efficient the more you use it.
Machine learning can go from overly simple models, such as the ones based on linear regressions, to complex ones, like deep models designed to deal with difficult problems that arise from unstructured data.
Enter deep learning
Deep learning is a sub-field of machine calling list learning that tries to create models that emulate human-decision making capabilities. There are dozens of architectures that have been used for anything from social media filtering to visual and voice recognition.