Major animal diseases pose a great threat to animal husbandry and human beings. With
the deepening of globalization and the abundance of data resources, the prediction and analysis of
animal diseases by using big data are becoming more and more important. The focus of machine
learning is to make computers how to learn from data and use the learned experience to analyze
and predict. Firstly, this paper introduces the animal epidemic situation and machine learning.
Then it briefly introduces the application of machine learning in animal disease analysis and
prediction. Machine learning is mainly divided into supervised learning and unsupervised learning.
Supervised learning includes support vector machines, naive bayes, decision trees, random forests,
logistic regression, artificial neural networks, deep learning, and AdaBoost. Unsupervised learning
has maximum expectation algorithm, principal component analysis hierarchical clustering
algorithm and maxent. Through the discussion of this paper, people have a clearer concept of
machine learning and an understanding of its application prospect in animal diseases.