There are 8 main steps:
- Frame Problem and Look at the Big Picture
- Get Data
- Explore data to gain insights
- Prepare the data to better expose the underlying data patterns to Machine Learning Algorithms
- Explore many different models and shortlist the best ones
- Fine-tune your model
- Present you solution
- Launch, monitor and maintain your system
Note that a ML project is only about 50~60% done when you’ve finally launched your model. It is important to keep in mind that, you want to get to step 8 as fast as possible and iterate this step as much as you can to achieve results and reduce unnecessary tasks.
References:
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition
