8/23/2021 0 Comments Machine Learning or Data Modeling? Machine Learning Classification and data modeling are two of the buzzwords that are widely used by most marketers. However, what is the difference between these terms? Are they similar or different? How can you make the most out of both data modeling and machine learning? Data modeling basically refers to an approach in business wherein data is processed through mathematical formulas to come up with predictions and estimates. The same approach is used in machine learning for it to become more effective. Data modeling primarily deals with mathematical data while machine learning applies more to information and numerical figures. Machine learning, however, can also deal with other concepts such as optimization. You can easily see the two types of processing data through the examples set by machine learning. With data modeling, the training data is considered as the basic input while in machine learning, they are more concerned with the result. These concepts may not be clear to the untrained eye, but they can be easily understood once you have undergone a training course on machine learning. There are several benefits in using data modeling in contrast to machine learning. Data modeling primarily deals with numbers and quantities, making it easier to process. With data modeling, there is no need to create maps, charts, and graphs manually which can be confusing and labor-intensive. Clustering Data can deal with high-level mathematics making it a good choice when dealing with more complicated problems. Machines, on the other hand, cannot process complex data. There are some differences between the two. With data modeling, it deals with educating the machine learning system on how to function with different types of data while in machine learning, the program relies on the user. Data modeling also uses traditional methods such as normal distribution, logistic regression, and the binomial model to learn patterns. On the other hand, machine learning usually deals with artificial intelligence or optimization where it uses reinforcement learning and genetic programming to train the machine on specific tasks. Machine learning, in some ways, is similar to how humans learn unlike with data modeling where the system has to undergo training for the machine to recognize patterns. This is not to say that machine learning is better than data modeling. However, data still plays a huge part in the success of a machine. In any case, both have their own advantages and disadvantages so depending on your business needs and budget, you can go for either one. Check out this article: https://www.encyclopedia.com/computing/dictionaries-thesauruses-pictures-and-press-releases/machine-learning to get more info on the topic.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |