We all know, deep learning is a branch or a direction of development of machine learning, which is based on a set of algorithms attempt to establish a high level abstract model using model architecture. There are friends to engage in R language, and I want to learn to use the depth comes in, you can choose "Deep Learning Essentials based on the R language" refer to the study.
"Deep Learning Essentials based on the R language" parameter in conjunction with the R language package introduces deep learning H2O, to help understand the concept of depth of learning. From the settings available in the R important deep learning package to begin, then turned to a neural network, forecasting and depth prediction models, all these models by actual cases of aid to achieve. After the success of the H2O package is installed, you will learn prediction algorithm. Concepts such as over-fitting the data interpretation, the abnormality data, and the depth of the prediction model. Learning concept design parameter adjustment and optimization models.
Deep Learning Essentials focuses on how the R language and deep learning neural network model or depth combine to solve practical application requirements. The book has six chapters, which introduced the depth of learning the basics of training a predictive model of how to prevent over-fitting, identify abnormal data, training content and adjust the depth of predictive models and optimization models.
"Deep Learning Essentials (based on the R language)" HD Chinese PDF, from catalogs and bookmarks, text can be copied; HD in English PDF, catalogs and bookmarks, text can be copied; the English version of the two can be compared to learning. Complete source code.
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