Machine learning (ML) is generally defined as data-driven technology mimicking intelligent human abilities, which bit by bit upgrades its accuracy from experience. It starts with gathering massive amounts of data, such as numbers, texts, images and so on. After training with the data, ML algorithms build a logical model to identify patterns through the least possible human intervention. With the help of sample training data, programmers test the model’s validity before introducing a new dataset. The more training data, the better the prediction.Machine learning (ML) is generally defined as data-driven technology mimicking intelligent human abilities, which bit by bit upgrades its accuracy from experience. It starts with gathering massive amounts of data, such as numbers, texts, images and so on. After training with the data, ML algorithms build a logical model to identify patterns through the least possible human intervention. With the help of sample training data, programmers test the model’s validity before introducing a new dataset. The more training data, the better the prediction.Electronics & Semiconductors[#item_full_content]