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Learning latent variables using self encoder Because there are many redundancies in the high-dimensional input space, it can be compressed into some low-dimensional variables. The self encoder was first introduced by Geoffrey Hinton et al. In the 1980s. Similar to the technology used to reduce the input dimension in traditional machine lea ...

Data pre filling has its own characteristics, and redundant and invalid data need to be pre selected according to different data formats. Data preprocessing is roughly divided into three steps: data preparation, data conversion and data output. Data processing is not only the basic link of system engineering, but also an effective means to impr ...

Exploratory Data Analysis EDA (Exploratory Data Analysis) analysis with python   show holy respect to python community, for there dedication and wisdom   Dataset related: First, UCL wine dataset: UCI data set is a commonly used standard test data set for machine learning. It is a database for machine learning proposed by the University of ...

Standard zoom 1 Normalization from sklearn.preprocessing import MinMaxScaler def mm(): """ normalization :return: """ mm = MinMaxScaler(feature_range=(2,3)) data = mm.fit_transform([[90,2,10,40],[60,4,15,45],[75,3,13,46]]) print(data) [[3. 2. 2. 2. ] [2. 3. 3. 2.83333333] [2.5 2.5 2.6 3. ]] Zoom to [2,3] Th ...

1. Trial matrix A = [ 1 2 ...

Author: Yan Yongqiang, algorithm engineer, Datawhale memberIn this paper, through the self built gesture data set, we use YOLOv5s detection, then train squeezenet to predict the key points of the hand through the open source data set, and finally judge the specific gesture through the angle algorithm between the fingers and display it. The four ...

1. Readme I have been using vscode for more than three years. Most of them write python programs and occasionally C + + programs, but they are not complex and do not involve other third-party libraries. Even if third-party libraries are involved, most of them write CMakeLists files first, and then compile and run it with the standard cmake... ...

brief introduction KNN(K Nearest Neighbors) It can be used for classification problems and regression problemsClassification problem and regression problem are divided into whether to take weight or not give an example introduce The existing categories are red triangles and blue squaresWhat type should the newly entered green dot belong t ...

catalogue 0. Links to related articles 1. General 2. Spark code 0. Links to related articles Algorithm article summary 1. General Use RFormula to select features listed in spark2 Version 1.0 only supports some R operations, including: ~ ','. ',': ',' + ', and ‘-‘. ~ separate target and terms Split labels and features + con ...

PyTorch chapter of Transformer source code interpretation chapter Word embeddingLocation codingLong attentionBuild Transformer Insert picture description here Word embedding Transformer is essentially an Encoder. Taking the translation task as an example, the original data set is composed of one line in two languages. In application, ...