popular machine learning algorithms

-3PO, Terminator. There is also a concept of "weak AI" (narrow ai). In short, "weak AI" can accomplish some specific tasks like human beings, possibly better than humans, for example, Pinterest service uses AI to classify images, Facebook uses AI to identify faces, and this is "weak AI". The above example is a case of the actual use of "weak AI", which has embodied some of the characteristics of human intelligence. How to achieve. Where the intelligence comes from. With a question we understand

that is difficult to classify receive increasing larger weights until the algorithm identifies a Model that correctly classifies these samples -applied Predictive Modeling, 2013Predictions is made by majority vote of the weak learners ' predictions, weighted by their individual accuracy. The most successful form of the AdaBoost algorithm is for binary classification problems and is called ADABOOST.M1.You can learn more on the AdaBoost algorithm in the post: Boosting and AdaBoost f

collaborative computing that is popular. Finally, I would like to introduce how to use this data with a large amount of data to build a very intelligent system, making our system more intelligent. We all know that statistical machine learning is based on data. The most important step is to collect and collect data. High-quality and large-scale data can help us b

first, gradient descent method In the machine learning algorithm, for many supervised learning models, the loss function of the original model needs to be constructed, then the loss function is optimized by the optimization algorithm in order to find the optimal parameter. In the optimization algorithm of machine

non-supervised learning:watermark/2/text/ahr0cdovl2jsb2cuy3nkbi5uzxqvdtaxmzq3njq2na==/font/5a6l5l2t/fontsize/400/fill/i0jbqkfcma==/ Dissolve/70/gravity/southeast ">In this way of learning. The input data part is identified, some are not identified, such a learning model can be used to predict, but the model first need to learn the internal structure of the data in order to reasonably organize the data to be

, Terminator.There is also a concept of "weak artificial intelligence (Narrow AI)". In short, "weak AI" can accomplish certain tasks like human beings, possibly better than humans, for example, Pinterest service uses AI to classify images, and Facebook uses AI to recognize faces, which is "weak AI".The above example is a case of "weak artificial intelligence", which already embodies some of the characteristics of human intelligence. How is it achieved? Where does this intelligence come from? Wit

The last three weeks of Andrew Ng's machine learning were recently followed by the linear regression (Linear Regression) and logistic regression (logistic Regression) models in machines learning. Make a note here.Also recommended a statistical study of the book, "Statistical Learning method" Hangyuan Li, Book short, on

lot of things, such as:1. Collect more data and let us have more spam and non-spam samples2. Message-based routing information develop a complex set of features3. The development of a series of complex features based on the message body information, including the processing of the truncated words4. Develop complex algorithms for detecting deliberate spelling errors (writing watch as W4tch)Among the options above, it is very difficult to decide which

In recent years, the popular Neural networks (neural network) and deep Learning (learning) are branches of machine learning (machines learning). In the definition of computer science, learning