What are the stages in machine learning?

The stages in machine learning are as follows:

1. Data collection — This is a very important step. To prepare a machine learning software, we need to collect related data.
2. Data preparation — The collected data may not be in a form to be entered directly into the algorithm. To make it compatible with the algorithm, we need to clean and transform it.
3. Selection of algorithm — There are many machine learning algorithms. We need to choose an appropriate machine learning algorithm as per our data and requirements.
4. Training — In this step, data is provided to the selected algorithm for training. By analysing and observing data, the algorithm learns its important features.
5. Evaluation — To check whether the model has learnt the features or not, we need to test it. At the time of testing, we check its accuracy and evaluate the performance of the algorithm.
6. Predict or deploy — If the testing performance of the model is good, then we can use it to make predictions.