This section is devoted to data, datasets and data collection.📋 📜 📄
What is a dataset? How can data be collected? What kind of things should you consider when working and collecting data? We will try to answers some of this questions here.
Data is a very important part of machine learning because it defines the kind of results you will get. As François Chollet, the author of Keras, a very popular framework to do machine learning in python describes:
Keep in mind that machine learning can only be used to memorize patterns that are present in your training data. You can only recognize what you've seen before. Using machine learning trained on past data to predict the future is making the assumption that the future will behave like the past. That often isn't the case. (Source)
You can also find some sample data bases in the ml5-data-and-training Github repository. They have been collected, cleaned, and in most cases labeled.