Post by account_disabled on Feb 28, 2024 8:52:55 GMT
The different applications. Examples of the application of Machine Learning in life are as follows . Application in the medical field For example detecting someones illness from the existing symptoms. Another example is detecting heart disease from electrocardiogram recordings. . In the field of computer vision Can be exemplified in the form of the application of face recognition and face labeling like on Facebook. Another example is the translation of handwriting into text. . At the source of information retrieval Examples are language translation using a computer voice to text and spam email filters.
Application Techniques to Data One technique for applying machine learning is supervised learning. As B2B Email List discussed previously machine learning without data cannot work. Therefore the first thing to prepare is data . into groups namely training data and testing data . The training data will later be used to train the algorithm to find a suitable model while the testing data will be used to test and determine the performance of the model obtained at the testing stage. From the model obtained we can make predictions which can be divided into two types depending on the type of output. If the prediction results are discrete it is called a classification process.
For example gender classification is seen from handwriting male and female output. Meanwhile if the output is continuous it is called a regression process. For example predicting the range of house prices in the city of Bandung output in the form of house prices. Basic Concepts and How Machine Learning Works Fundamentally the way machine learning works is that it learns like humans by using examples and after that it can answer a related question. This learning process uses data called a train dataset . In contrast to static programs machine learning was created to form programs that can learn on their own. From this data the computer will carry out.
Application Techniques to Data One technique for applying machine learning is supervised learning. As B2B Email List discussed previously machine learning without data cannot work. Therefore the first thing to prepare is data . into groups namely training data and testing data . The training data will later be used to train the algorithm to find a suitable model while the testing data will be used to test and determine the performance of the model obtained at the testing stage. From the model obtained we can make predictions which can be divided into two types depending on the type of output. If the prediction results are discrete it is called a classification process.
For example gender classification is seen from handwriting male and female output. Meanwhile if the output is continuous it is called a regression process. For example predicting the range of house prices in the city of Bandung output in the form of house prices. Basic Concepts and How Machine Learning Works Fundamentally the way machine learning works is that it learns like humans by using examples and after that it can answer a related question. This learning process uses data called a train dataset . In contrast to static programs machine learning was created to form programs that can learn on their own. From this data the computer will carry out.