Mtcnn.com receives about 2723 visitors in one month. That could possibly earn $13.62 each month or $0.45 each day. Server of the website is located in the United States. Mtcnn.com main page was reached and loaded in 0.8 seconds. This is a good result. Try the services listed at the bottom of the page to search for available improvements.
Is mtcnn.com legit? | |
Website Value | $246 |
Alexa Rank | 1718058 |
Monthly Visits | 2723 |
Daily Visits | 91 |
Monthly Earnings | $13.62 |
Daily Earnings | $0.45 |
Country: United States
Metropolitan Area: Los Angeles
Postal Reference Code: 90012
Latitude: 34.0729
Longitude: -118.2606
HTML Tag | Content | Informative? |
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Title: | Zero Point Intelligence-TensorFlow, caffe framework, artificial intelligence community | |
Description: | artificial intelligence community, providing TensorFlow, caffe, Network, recommended algorithm one-stop solution | |
H1: | zero point intelligence | Is it informative enough? |
H2: | 】 Loss Function or Cost Function | Is it informative enough? |
H3: | Latest Release | Is it informative enough? |
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Loss Function or Cost Function - Zero Intelligence The |
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loss function is used to calculate the degree of deviation between the model's predicted value and the true value. Unlike the cl ification problem, the regression problem solves the prediction of specific values. For example, house price forecasts, sales forecasts, etc. are all regression issues. What these problems need to predict is not a pre-defined category, but an arbitrary real number. The neural network that solves the regression problem generally has only one output node, and the output value of this node is the predicted value. For regression problems, the most commonly used loss function is the mean square error (MSE: mean sequare error). It is defined as follows: where yi [censored]
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Loss Function or Cost Function |
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Zero Intelligence Artificial Intelligence Community, plus Q Group: 469331966 |
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Related Recommendations |
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regression evaluation index MSE, RMSE, MAE, R-Squared-zero intelligence |
Description |
Foreword The evaluation index of the cl ification problem is the accuracy rate, then the evaluation indicators of the regression algorithm are MSE, RMSE, MAE, R-Squared. The following describes the mean square error (MSE) MSE (Mean Squared Error) called the mean square error. Look at the formula image.png where y is on the test set. Use the true value - the predicted value and then square the sum after the sum. If you look at this formula and feel it is familiar, this is not the loss function of linear regression! ! ! Yes, in the linear regression [censored]
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regression evaluation indicators MSE, RMSE, MAE, R-Squared |
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uses tensorflow session to implement type conversion - zero point intelligence |
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The most common method for normalizing offline data is one-hot coding. The principle of one-hot coding is explained in detail in the previous article. Narration. There are various ways to implement one-hot encoding. There are no more than three ways to use Python's own functions. However, these kinds of transcoding methods implemented by Python are still a bit bersome, so here is a very simple conversion. To the one-hot encoding method, one line of code will get it! #!/usr/bin/python # -*- coding: [censored]
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Using tensorflow session to achieve type conversion |
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Decision Tree: An algorithm that works like a human brain - Zero Smart |
Description |
Sunlight p es through the leafy tree, Jeremy Bishop's decision tree on Unsplash is one of the most commonly used algorithms in machine learning, mainly Used for cl ification and also for regression problems. Whenever we ask ourselves a question before making a decision, our brain works like a decision tree. For example: Is it cloudy outside? If so, I will bring an umbrella. When training data sets to cl ify variables, the idea of a decision tree is to divide the data into smaller data sets based on specific feature values until the target variables all belong to one category. When the human brain decides to choose based on experience (ie cloudy sky) [censored]
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Decision Tree: an algorithm that works like a human brain |
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Zero Intelligence - TensorFlow, caffe learning framework, artificial intelligence community [censored]
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artificial intelligence community, providing learning TensorFlow, caffe, neural network, recommended algorithm one-stop solution [censored]
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Zero point intelligence |
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[Today's point of view] Loss Function or Cost Function |
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latest release |
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