most common machine learning algorithms

Bayesian Introduction Bayesian learning Method characteristic Bayes rule maximum hypothesis example basic probability formula table Machine learning learning speed is not fast enough, but hope to learn more down-to-earth. After all, although it is it but more biased in mathematics, so to learn the rigorous and thoroug

larger (because the more difficult perfectly fit), J (CV) smaller (because the more accurate), You know what I mean?Then we are high Bias and high variance to see how to increase the number of training set, that is, M, is it meaningful?!Underfit high bias: adding M is useless!Overfit High Variance: Increasing m makes the gap between J (train) and J (CV) decrease, which helps performance improve!Come on, do the problem:As can be seen from the graph, increasing the number of training data is usef

from:http://blog.jobbole.com/60809/After understanding the machine learning problems that we need to solve, we can think about what data we need to collect and what algorithms we can use. In this article, we'll go through the most popular machine learning

level as these mature programming languages. When we switch to the relative view of data on Indeed.com, this is easier to find. Fifth, although Julia's popularity is not obvious, there must be an increasing trend. Will Julia become a popular programming language for machine learning and data science? We will tell you in the future. If we ignore Scala and Julia so that we can focus on the growth of other

of human learning mechanisms, such as physiology and cognitive science. It establishes computational models or cognitive models for human learning, and develops various learning theories and methods, study general learning algorithms and perform theoretical analysis to esta

As the name implies, the purpose of machine learning is to allow machines to have the ability to learn, understand, and comprehend things similar to human beings. Imagine how important it is for a patient's recovery if a computer can summarize and sum up a large number of cancer treatment records, and be able to give appropriate advice and advice to a physician. In addition to the medical field, financial s

vectors or the longer the length of the vector, the following to deal with the length of the vector.Using the nature of the PLA's "Fault only Update", in the case of making mistakes, through the above deduction, the final conclusion is that the square of WT length increases the square of xn longest length after each update.Using the conclusion of the first proof, the derivation process is as follows:The above is known as three conditions, there are two points to be explained:1) Because the valu