Up to this point, you already know how synthesis ai machine learning works, the datasets for machine learning, and also the various methods of using it. But, what are examples of machine learning practices in the real world like? Of course, there are many examples that you can find.

1. Health sector – Machine learning can be applied to devices that function to analyze patient health. In addition, this technology can also use historical data to predict potentially emerging diseases.

2. Transportation sector – Machine learning can also be used to analyze the most efficient routes for logistics or public transportation companies. Thus, obstacles such as getting stuck in traffic jams, wrong roads, and the like can be prevented.

3. Governance – Problems with impersonation can be addressed with machine learning. Therefore, this technology can also be used in the government sector.

4. Finance – Investment and banking businesses can take advantage of machine learning to identify the risk profile of each customer. Thus, this can prevent risks related to fraud or default.

5. Retail industry – Retail companies can use machine learning for many things. Starting from analyzing prices, planning procurement of goods, to offering the right product recommendations to potential customers. The analogy is like this, imagine that there is a scale on the right side of which there is an iron weighing 3 kg. Then, based on observation, you know that by placing a 3 kg iron on the left side, the scales will be balanced.

Well, does it mean that placing a 3 kg iron on the left side of the scale will always make it balanced? Certainly not. There are times when new loads are stored on the right side. Whether it’s 5 kg iron or even 10 kg. So, you have to re-observe so that the scales can be balanced again. Likewise with algorithms. There are times when new data appears, so the model must be re-evaluated to keep the results accurate.