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11.1 What to do first11.2 Error AnalysisError measurement for class 11.3 skew11.4 The tradeoff between recall and precision11.5 Machine-Learning data 11.1 what to do firstIn the next video, I'll talk about the design of the machine learning system. These videos will talk about the major problems you will encounte

Azure Machine Learning ("AML") is a Web-based computer learning service that Microsoft has launched on its public cloud azure, a branch of AI that uses algorithms to make computers recognize a large number of mobile datasets. This approach is able to predict future events and behaviors through historical data, which is significantly better than traditional forms

Machine learning is divided into supervised machine learning, unsupervised machine learning, and semi-supervised machine learning. The crite

one, factor decomposition machineFMthe Modelfactor decomposition Machine (factorization machine, FM) is bySteffen Rendlea machine learning algorithm based on matrix decomposition is proposed. 1, Factor decomposition machineFMThe advantagesfor factor decomposition machinesFM, the most important feature is that the spars

neighbor point, and then can establish a neighbor map, so calculate the distance between two points of the problem, The transition becomes the shortest path problem (Dijkstra algorithm) between two points on the nearest neighbor graph.So what is the ISOMAP algorithm? In fact, it is a variant of the MDS algorithm, the same idea as the MDS, but in the calculation of the distance of the high-dimensional space is the geodesic distance, rather than the real expression of the European distance betwee

previous article Python machine learning "Getting Started"Body:In the previous introductory article, we mainly introduced two algorithms for machine learning tasks: supervised learning and unsupervised learning. Among them, the t

Machine learning Notes (iii) multivariable linear regression Note: This content resource is from Andrew Ng's machine learning course on Coursera, which pays tribute to Andrew Ng. One, multiple characteristics (multiple Features)The housing price problem discus

Recently is a period of idle, do not want to waste, remember before there is a collection of machine learning link Andrew ng NetEase public class, of which the overfiting part of the group will report involved, these days have time to decide to learn this course, at least a superficial understanding.Originally wanted to go online to check machine

randomly groups the data to the extent that training intensive accounts for 70% of the original data (this ratio can vary depending on the situation), and the test error is used as the criterion when selecting the model. The question comes from the Stanford University Machine Learning course on Coursera, which is described as follows: the size and price of the

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