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Tip: after the article is written, the directory can be generated automatically. Please refer to the help document on the right for how to generate it 1, Data sorting 1. sort If the direction is not indicated in sort, it will be sorted in ascending order by defaultIn multidimensional tensors, sorting is not in the global case, but in t ...

Original text from:< Old cake explanation neural network > catalogue I Normalization and inverse normalization II Practical examples III Complete code example IV Inverse normalization of network expression In order to facilitate better network training, the input and output data will be normalized before training. After training, ...

In the NLP task of automatic text understanding, named entity recognition (NER) is the primary task. The function of NER model is to identify named entities in text corpus, such as person name, organization, location, language and so on.NER model can be used to understand the meaning of a text sentence / phrase. It can recognize the words that ...

Convolutional neural network (CNN) Learning objectives Understand the composition of convolutional neural networkKnow the principle and calculation process of convolutionUnderstand the function and calculation process of pooling There are two problems in image processing using fully connected neural network: The amount of data to be p ...

Visualization helps to explain and understand the internal structure of deep learning model. Through the visualization of the model calculation diagram, we can find out how the neural network is calculated. The visualization of the model mainly includes the following aspects: How many layers does the model haveInput and output shapes of each l ...

In this article, first briefly explain what the mixed density network (MDN) is, then build the MDN model using Python code, and finally use the built model for multiple regression and test the effect.regression"Regression prediction modeling is to approximate the mapping function (f) from input variable (X) to continuous output variable (y ...

Network model construction of deep learning 1, Inherit Module class construction model Module class is a model construction class provided in nn module. It is the base class of all neural network modules. We can inherit it to define the model we want. The following inherits the module class to construct the multi-layer perceptron menti ...

Detectron quick start official Colab Notebook Read the Getting Started section on: 1. Use the pre trained Detectron2 model To download an image, we need to create a detectron2 config, and then create a Default Predictor according to the config for single image reasoning. cfg = get_cfg() # Get Default Config # According to mask_ rcnn_ R_ 50_ ...

This practical project is based on the dataset of Lending Club [dataset address: https://github.com/H-Freax/lendingclub_analyse/data/ ] This practical project is based on Colab environment brief introduction This practical project of data analysis is divided into two parts. The first part mainly introduces the Baseline method based on Lig ...

Image features Similar to text features, image features are also a kind of data that is very difficult to mine by gradient lifting tree model. At present, image related problems, such as image classification and image segmentation, are almost neural network-based models. However, in some multimodal problems, such as commodity search recommen ...