Best practices for machine learning

In the previous sections, we saw how to perform feature engineering to enhance the performance of our machine learning system. Now, we are going to discuss some tips and best practices to build robust intelligent systems. Let's explore some of the best practices in the different aspects of machine learning projects.

Information security datasets

Data is a vital part of every machine learning model. To train models, we need to feed them datasets. While reading the earlier chapters, you will have noticed that to build an accurate and efficient machine learning model, you need a huge volume of data, even after cleaning data. Big companies with great amounts of available data use their internal datasets to build models, but small organizations, like startups, often struggle to acquire such a volume of data. International rules and regulations are making the mission harder because data privacy is an important aspect in information security. Every modern business...