Major Problems of Machine Learning Datasets: Part 1

Data play a key role in machine learning, and the better and more relevant data you have, the more accurate the model you will build. Getting the perfect data, however, is still a dream for many data scientists. A lot of data comes from web scraping, APIs and other external sources, and most real-world datasets will just look like an ugly stack of information, at least at first. However, data will speak for itself, if you keep it organized. In this blog, I would love to share some major problems that occur with many supervised machine learning datasets, as well as how to deal with them.