Machine Learning 101

There are basically 4 steps in developing a ML model or application. Teaching data is a data set representative of the information to be ingested by the machine learning application to solve the challenge is built to fixed. In certain situations, the teaching data is labeled data – designed to select classifications and features that the model will have to recognize. Other data sets are unlabeled; thus the model will have go remove those characteristics and allocate categorizations on its own. Nonetheless, the teaching data must be adequately prepared and scanned for anomalies or falsities that could affect the training.