A Beginner’s Guide to Machine Learning for Quality Professionals

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Machine learning is a field of artificial intelligence that allows computers to perform tasks normally requiring human expertise. Machine learning aims to create algorithms that enable computers to complete certain tasks without explicit instructions.

Machine learning has the potential to improve quality management processes for organizations greatly. However, we have seen very limited use of this technology in the field of Quality Management. In this post, we will explore the basics of machine learning and discuss the kinds of problems that can be solved by using it.

What Is Machine Learning?

Machine learning is an area of computer science that deals with algorithms that can learn from data. It uses statistical methods to analyze large amounts of information to predict future events.

The process involves feeding data through a set of rules or models to make predictions about future outcomes. Machine learning is a powerful tool that can be used to make accurate predictions about the future.

Main Types of Machine Learning Models

There are two main types of machine learning models: supervised, unsupervised, and reinforcement.

Supervised Learning: This type of machine learning is used to learn from a set of labelled data sets. For example, you might have a labelled data set with pictures of cars and their descriptions. The machine learning algorithm would use these pictures as examples to learn how to recognize cars.

Unsupervised Learning: This type of machine learning is used to learn from an unlabeled data set. An unlabeled data set typically consists of data that has not been assigned labels. For example, you might have an unlabeled data set that includes just the pictures of cars without their description. The machine learning algorithm would use these pictures to group these cars into different categories. Unsupervised learning is useful when there is no previous knowledge of the data.

Both supervised and unsupervised learning algorithms can be used for several different purposes, including:

  • Classification: This type of machine learning is used to identify the type of object in a picture, such as a car or a person.
  • Clustering: This type of machine learning is used to group similar objects together.
  • Forecasting: This machine learning type is used to predict future events. For example, you might use it to predict how sales will be for the next month based on previous data sets.

In addition to supervised and unsupervised learning models, other machine learning models include Reinforcement Learning, Deep Learning, and Neural Networks.

How Can Machine Learning Be Used To Improve Quality?

The most common application of machine learning is improving product quality. Here are some examples:

1) Predicting defects before they occur

2) Identifying counterfeit products

3) Detecting fraud

4) Optimizing production lines

5) Finding trends

6) Making better decisions

7) Building intelligent systems

8) Analyzing big data

9) Predicting consumer behaviour

Conclusion

With the right tools and techniques, machine learning can be used to improve the quality of your products or services. It can also save you time and money while improving your organization's overall performance.






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