We have already seen a very simple example and used it to explain some basic concepts. In the next chapter, we are going to explore more complex models. We restricted ourselves to a very small dataset, just for clarity and to start our journey towards mastering machine learning with an easy task. There are some general considerations that we need to be aware of when working with machine learning models to solve real problems:
- The amount of data is usually very large. In fact, a larger dataset helps to get a more accurate model and a more reliable prediction. Extremely large datasets, usually called big data, can present storage and manipulation challenges.
- Data is never clean and ready to use, so data cleansing is extremely important and takes a lot of time.
- The number of features required to correctly represent a real-life problem...
