kaggle machine learning datasets

Original: Image classification in 5 MethodsAuthor: Shiyu MouTranslation: He Bing Center Image classification, as the name suggests, is an input image, output to the image content classification of the problem. It is the core of computer vision, which is widely used in practice. The traditional method of image classification is feature description and detection, such traditional methods may be effective for some simple image classification, but the traditional classification method is overwhelmed

: Perceptron Neural Networks (Perceptron neural network), reverse transfer (back propagation), Hopfield network, Self-organizing mappings (self-organizing map, SOM).Back to Top2.11 Deep LearningDeep learning algorithm is the development of artificial neural network. In the near future won a lot of attention, especially Baidu also began to exert deep learning, is in the domestic caused a lot of concern. In t

clustering algorithm tries to find the intrinsic structure of the data in order to classify the data in the most common way. Common clustering algorithms include the K-means algorithm and the desired maximization algorithm (expectation maximization, EM).Association Rule LearningAssociation rule Learning finds useful association rules in a large number of multivariate datasets by finding rules that best exp

common way. Common clustering algorithms include the K-means algorithm and the desired maximization algorithm (expectation maximization, EM).Association Rule LearningAssociation rule Learning finds useful association rules in a large number of multivariate datasets by finding rules that best explain the relationship between data variables. Common algorithms include Apriori algorithm and Eclat algorithm.Art

structure of the data in order to classify the data in the most common way. Common clustering algorithms include the K-means algorithm and the desired maximization algorithm (expectation maximization, EM).Association Rule Learning　　Association rule Learning finds useful association rules in a large number of multivariate datasets by finding rules that best expla

algorithms typically merge input data by either a central point or a hierarchical approach. So the clustering algorithm tries to find the intrinsic structure of the data in order to classify the data in the most common way. Common clustering algorithms include the K-means algorithm and the desired maximization algorithm (expectation maximization, EM).Association Rule LearningAssociation rule Learning finds useful association rules in a large number o

Brief History of the machine learningMy subjective ML timelineSince the initial standpoint of science, technology and AI, scientists following Blaise Pascal and Von Leibniz Ponder AbouT a machine which is intellectually capable as much as humans. Famous writers like JulesPascal ' s machine performing subtraction and summation–1642Machine

, B is the model parameter, W is the weight or weight vector, B is biased, W X is expressed as the inner product. Geometrically, the W x+b=0 corresponds to a super-plane of the feature space, W is the normal vector of the super-plane, and B is the intercept of the super-plane. That is, finding a hyper-plane separates the positive and negative instances of the data.2. Perceptual Machine Learning Strategy2.1

is a kind of pattern matching algorithm simulating biological neural network. Typically used to solve classification and regression problems. Artificial neural network is a huge branch of machine learning, there are hundreds of kinds of different algorithms. (Deep learning is one of these algorithms, which we will discuss separately), important artificial neural

order to classify the data in the most common way. Common clustering algorithms include the K-means algorithm and the desired maximization algorithm (expectation maximization, EM).Association Rule LearningAssociation rule Learning finds useful association rules in a large number of multivariate datasets by finding rules that best explain the relationship between data variables. Common algorithms include Ap