The machine learning journey

Machine learning (ML) is a significant part of Artificial Intelligence (AI). Along with data science (DS) and deep learning (DL), ML plays a crucial role in all aspects of data extraction, transformation and loading (ETL). ML is also fundamental in all aspects of training, evaluating, tuning, operationalizing and maintaining AI models. The following Venn diagram shows the relations between the practices of AI, ML, DL and DS.

AI and ML Venn

I have created a flowchart-type mindmap which summarizes all phases of the machine learning journey, from dataset creation to AI model maintenance. These phases at high-level are the following:

  • Step 1 - Define the business problem and desired outcome
  • Step 2 - Formulate the ML problem
  • Step 3 - Setup the ML infrastructure
  • Step 4 - Work with data in ML workspace(s)
  • Step 5 - Implement ML algorithm(s)
  • Step 6 - Train and test ML model(s)
  • Step 7 - Evaluate and tune ML model(s)
  • Step 8 - Operationalize ML model(s)
  • Step 9 - Maintain ML model(s)

The free mind map can be found at: