24 Sep Steps to Build a Machine Learning Model

Widely a process is followed to build a Machine Learning Model. Let us now see the steps to build a model in Machine Learning:

• Build a Model: For the Machine Learning model, select an algorithm.
• Train the Model: According to the requirements, train the model using the training dataset.
• Model Testing: We all know why testing is important. Here, the ML model is tested using the new data i.e. the model accuracy is tested using the test data.
• Applying/ Deplot the model: After the testing is complete, apply the changes you need to make considering the test results. Make the required changes and apply the final model for real-time projects.

The below figure will make the steps clearer:

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Read More:

• Overview of Machine Learning
• Applications of Machine Learning
• Machine Learning vs Deep Learning
• What is a Machine Learning Model
• Train/ Test in a Machine Learning Model
• Inductive vs Deductive Machine Learning
• Bagging vs Boosting in Machine Learning
• What are Large Language Models (LLMs)
• Artificial Intelligence vs Machine Learning vs Data Science vs Deep Learning
• Types of Deep Learning
• Techniques for implementing Generative AI
• What are Transformers in Deep Learning