Machine Learning Best Practices
After working on multiple projects covering important machine learning concepts, techniques, and widely used algorithms, you have a broad picture of the machine learning ecosystem, as well as solid experience in tackling practical problems using machine learning algorithms and Python. However, there will be issues once we start working on projects from scratch in the real world. This chapter aims to get us ready for it with 21 best practices to follow throughout the entire machine learning solution workflow.
We will cover the following topics in this chapter:
- Machine learning solution workflow
- Best practices in the data preparation stage
- Best practices in the training set generation stage
- Best practices in the model training, evaluation, and selection stage
- Best practices in the deployment and monitoring stage
