#MLConcepts: What is a Machine Learning Pipeline?
Jun 26, 2023
This question will usually pop up at the start of a Machine Learning journey.
In very simple words machine learning pipeline is an orchestration of connected activities, used to perform machine learning tasks.
They are usually performed using the following stages:
- Acquire Data
- Preprocessing
- Feature Engineering
- Model Training
- Model Evaluation
- Model Tuning
- Deployment
These steps remain consistently common in any type of AI/ML project.
How is it implemented?
The most usual way of implementing ML Pipelines is Iron Python Notebooks.
Tools at your disposal
A number of common tools are available to implement ML Pipelines and they can be either installed on your workstation or can be used online. Some examples are:
Installing on your workstation:
Anaconda — Here
Available Online and No deployments needed:
Google Collab — Here
