deep learning framework

. This time was basically the world of SVM and boosting algorithms. However, an infatuated old Mr. Hinton persisted and eventually (together with others, bengio, Yann. lecun, etc.) developed a practical deep learning framework. Deep Learning differs from traditional neural n

[Deep Dive into the. NET platform] talking about the. NET Framework primitive type,. netframework What is a primitive type? Beginners may have seldom heard of this term, but the most commonly used is the primitive type. Let's take a look at the following two lines of code: System.Int32 a = 5;int a = 5; Both the above two lines of code declare an int type variable, but we usually use the second method whe

He admired the bronze teacher for a long time, and when he learned that he had written a book on learning methods, "The art of deep learning", he bought the first ebook I paid for in my life on the Amazon China website.This reading note is not exactly in accordance with the original book narrative sequence excerpt, but through my modification and collation.Readin

Dry Goods | The latest development of speech recognition framework--deep full sequence convolution neural network debut2016-08-05 17:03 reprinted Chenyangyingjie 1 reviewsIntroduction: At present the best speech recognition system uses two-way long-term memory network (LSTM,LONGSHORT), but the system has high training complexity, decoding Singo problems, especially in the industry's real-time recognition sy

, and then establish the expression, For example, these low-level expressions of linear or nonlinear combinations, and then repeat the process, and finally get a higher expression.Deep learning is able to get a better representation of the feature of the data, and because of the level of the model, many parameters, capacity enough, so the model has the ability to represent large-scale data, so for the image, This feature is not obvious (requires manua

difficult to benefit from end-to-end learning methods; The DCF algorithm is less than two: Model updating adopts the method of sliding weighted averaging, which is not the optimal updating method, because once the noise is involved in the update, it is likely to lead to the drift of the model, so it is difficult to simultaneously get the stability and adaptability of the model. Improvement One: The model of DCF algorithm is regarded as convolution fi

Contact Way: 860122112@qq.com DQN (Deep q-learning) is a mountain of deep reinforcement learning (Deep reinforcement LEARNING,DRL), combining deep