Developing Machine Learning Pipelines

Even the most experienced Data Scientists are not always familiar with the best practices involved with developing a Machine Learning pipeline. There is a lot of confusion about what steps should be involved, what should be their sequence and, in general, how to ensure that the insights you create are accurate and valuable. There is also a very limited number of good resources describing a practical and correct approach. However, after many data science projects, you begin to realise the approach to building a pipeline always remains the same. Machine Learning pipelines are modular, and, depending on the situation, some steps can be added or skipped.