Machine learning applications

Information retrieval is an area where machine learning is vastly applied in the industry. Some examples include Google News, Google target advertisements, and Amazon product recommendations.

Google News uses machine learning to categorize large volumes of online news articlesL:

The relevance of Google target advertisements can be improved by using machine learning:

Amazon as well as most of the e-business websites use machine learning to understand which products will interest the users:

Even though information retrieval is the area that has commercialized most of the machine learning applications, machine learning can be applied in various other areas, such as business and health care.

Machine learning is applied to solve different business problems, such as market segmentation, business analytics, risk classification, and stock market predictions.

A few of them are explained here.

Market segmentation (clustering)

In market segmentation, clustering techniques can be used to identify the homogeneous subsets of consumers, as shown in the following figure:

Take an example of a Fast-Moving Consumer Goods (FMCG) company that introduces a shampoo for personal use. They can use clustering to identify the different market segments, by considering features such as the number of people who have hair fall, colored hair, dry hair, and normal hair. Then, they can decide on the types of shampoo required for different market segments, which will maximize the profit.

Machine learning is heavily used in medical image processing in the health care sector. Using a mammogram for cancer tissue detection is one example of this.

Using a mammogram for cancer tissue detection

Classification techniques can be used for the early detection of breast cancers by analyzing the mammograms with image processing, as shown in the following figure, which is a difficult task for humans due to irregular pathological structures and noise.