Binary Classification (二元分類) Binary or binomial classification is the task of classifying the elements of a given set into two groups (predicting which group each one belongs to) on the basis of a classification rule. Contexts requiring a decision as to whether or not an item has some qualitative property, some specified characteristic, or some typical binary classification include:
Medical testing to determine if a patient has certain disease or not – the classification property is the presence of the disease.
Information retrieval, namely deciding whether a page or an article should be in the result set of a search or not – the classification property is the relevance of the article, or the usefulness to the user.
Q: Why do we have to use Python? A: Python is an open-source language, anyone can use it from anywhere in the world. It is widely used in academics (research labs) or in the industry. It has a useful library "Numpy" that makes math operations very easy. Python has several deep learning frameworks running on top of it (Tensorflow, Keras, PaddlePaddle, CNTK, Caffe, ...) and you are going to learn some of them. It is also easy to learn. Furthermore, we believe Python has a good future, as the community is really active and builds amazing stuff.