Step by Step Guide to Building a Machine Learning Model

Below I outline seven important steps that start with thinking about ML Model building to fully deploying a ML model.

This is the first step in getting a better idea of what is trying to be achieved by building a ML model.

2. Choose and Explore Data

This is the process of finding the input data for the model.

3. Prepare and Clean Data

As the model will be learning the relationship between the input and output data, it is important the input data is accurate and represents the reality of the problem trying to be solved.

4. Choose the type of Model

The type of ML model chosen will depend on your understanding of the data and problem.

5. Split Data, Perform Cross Validation

This step ensures that the data can perform well on new data.

6. Model Optimisation

This is the process of tweaking the model to improve the accuracy of it.

7. Deploy the ML Model

Now the model building is finished the user would want to deploy the model to start making use of it.

Related posts:

If your company is dedicated to the creation of content for different regions of the world, surely you already know about text-to-speech software. They have become more and more popular but the truth…

Search engine optimisation (SEO) has been a crucial aspect of online marketing for many years. Its primary goal is to enhance a website’s visibility in search engine results pages (SERPs) and attract…

Misaligned or crooked teeth make people feel the most uncomfortable. They feel a bit weird while smiling at the photographs. And another expression might not make them happy at all. In these…