What is the process involved in machine Learning?

The process involved in Machine learning includes seven different steps. They are briefly explained below.

Step 1- Data Gathering: Data gathering is the primary step in the process of Machine Learning. In order to perform any operation or to play and analyze around with the data, we need to gather the data.

Step 2 - Data Pre-processing: After data gathering, it is not clear and easy to understand. Hence the data needs to be processed and converted into information before performing any task or operation using the data.

Step 3 - Choosing the right algorithm /model: In this world of advancements, there are many different modules or algorithms. You need to ensure that you are choosing the suitable algorithm that best suits your requirements.

Step 3 - Train the model: After performing the above three phases- data gathering, data pre-processing and choosing the right algorithm or model, you will need to train the model.

Step 4 - Test the model: Once the training of the model is done, you will need to test the model if it is working fine or not. Though it works well or not, you will need to re-train the model. As re-training of the model is retaking place, it is considered as an iterative process.

Step 5 - Tune the model: Once the re-trained model has completed the testing stage, the next step is to check for the accuracy. It is your responsibility to check how accurately the model is working. In the starting, it would not be as accurate as expected. Hence, you will need to tune the model accurately to ensure that the accuracy is met as per the client requirements. Tuning the model can include aspects like applying filters and adding additional tiny inputs that would bring up more efficiency. Machine learning is one of the best technology with a high scope and development in terms of career.