Now, more and more large data hot, hot in big data, but also the birth of a lot of hot words on big data. Need to tell you is that big data hot words are from the previous basic technology development through the formation, although the content is not new, but only mastered this knowledge we can work better cope with big data processing, let big data'll tell you about the algorithm and deep learning.
1. depth study
When we see depth study of the word, we may think of further study, but it is not, the artificial neural network concept comes from the depth of learning. Deep learning is a new field of machine learning research, their motivation is to build, simulate the human brain to analyze learning neural network, which mimics the mechanism of the human brain to interpret the data, such as images, sound and text. Thus, in many areas the summary can not do without deep learning. Containing multiple hidden layers of the multilayer perceptron learning is a deep structure. Attribute category indicates deep learning or more abstract features formed by the combination of high-level low-level features, to find a distributed representation of the characteristic data. And the source of deep learning is presented by Hinton et al. Convinced of the proposed network based unsupervised training algorithm greedy layer by layer, bring hope to solve the optimization problem of deep structure, and then put forward a multi-layer automatic encoder deep structure. In addition convolution neural network Lecun et al is the first truly multi-layer structure learning algorithm, which uses spatially relative reduction in the number of parameters to improve training performance.
2. Algorithms
The word algorithm is not a new term, but the algorithm is still a very important technology, then what is the algorithm do? Problem-solving algorithm means accurate and complete description of the program, a series of clear instructions to solve the problem, the algorithm represents a policy mechanism to solve the problem described in a systematic way. That is, a certain specification can be input to obtain the required output within a limited time. The pros and cons of an algorithm can use the space complexity and time complexity of the measure. The use or design algorithms are able to test the level of a technical engineer. If an algorithm is defective, or not suitable for a problem, the implementation of this algorithm will not solve the problem. Different algorithms might use a different time, space or efficiency to accomplish the same task.
In this article we tell you about the big data analysis algorithms and knowledge of the depth of learning. In fact, Big Data or artificial intelligence, learning algorithms and depth of knowledge is very important, so we are carrying big data for learning when we must learn the contents of this area, the last hope this article will help you better understand Big Data.