Programmer Think

Logistic Regression Advantages: low computational cost, easy to understand and implement. Disadvantages: it is easy to under fit, and the classification accuracy may not be high. Applicable data types: numerical data and nominal data. Main idea: according to the existing data, the classification boundary resume regression formula is used to ...

1. Preface The data import of Pytorch depends on torch utils. data. Dataloader and torch utils. data. Dataset (or torch.utils.data.IterableDataset). 2. torch.utils.data.DataLoader learning In torch utils. As mentioned in the official data document, torch utils. data. Dataloader is the core tool of pytorch data import. It returns an iteratabl ...

Background knowledge required for reading this article: logarithmic probability regression algorithm (I), conjugate gradient method, and a little programming knowledge1, Introduction   continue with a log probability regression algorithm (I), which introduces two methods to optimize the cost function of log probability regression - Gr ...

tf.keras.layers.Conv2D() function Conv2D (2D convolution) This layer creates a convolution kernel, which is convoluted with the input of this layer to produce an output tensor When this layer is used as the first layer of the model, the keyword parameter input is provided_ Shape (integer tuple, excluding sample axis, no need to write batch_s ...

[Source Parsing] Deep Learning Distributed Training Framework horovod(20) - Elastic Training Operator 0x00 Summary Horovod is a distributed training framework based on ALReduce. Horovod is widely used in data parallel training due to its support for mainstream deep learning frameworks such as TensorFlow, PyTorch, and communication optimiz ...

1. For example: (1) I want to locate myself. I can ask five people where to judge the distance between us Judge your distance by your neighbors (2) Seven films are given to judge whether they are love films or action films, the distance between one film and other films, and which type they belong to. Through the distance from the unknown fi ...

1. KNN Algorithm principle: k elements are randomly selected from D as the respective centers of k clusters;Calculate the dissimilarity of the remaining elements to the center of k clusters, and classify these elements into the cluster with the lowest dissimilarity;According to the clustering results, the respective centers of k clusters are ...

Write a blog for the first time and share with you the gender recognition you just learned (not images). Judge gender according to a person's height, weight and gender 1. Backgroundneural network It has the functions of prediction, fitting and classification Neural networks connect a bunch of neurons together. 2. Objectives Through the corre ...

Classification method based on probability theory: Naive Bayes Advantages: it is still effective in the case of less data (but the accuracy is also inexhaustible), and can deal with multi category problems. Disadvantages: it is sensitive to the way data is input. Applicable data type: nominal data. Pre knowledge: conditional probability, Bay ...

preface What is GPU? GPU (Graphic Process Units). It is a single-chip processor, which is mainly used to manage and improve the performance of video and graphics. GPU accelerated computing refers to the use of graphics processor (GPU) and CPU to speed up the running speed of applications.Why use GPU? Deep learning involves many vector or multi ...