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Author: Han Xinzi@ShowMeAITutorial address: http://www.showmeai.tech/tutorials/56Article address: http://www.showmeai.tech/article-detail/77Notice: All Rights Reserved. Please contact the platform and the author for reprint and indicate the source1.Python listSequence is the most basic and common data structure in Python. Each element in the se ...

Anomaly detection Establish a model p, which is similar to the probability of normal situation. If it is less than a certain value, it is considered to be abnormal. Application scenario Fraud detectionAbnormal parts detectionData center computer working condition monitoring Gaussian distribution parameter estimation Let's give you a ...

Author: Han Xinzi@ShowMeAITutorial address: http://www.showmeai.tech/tuto...Article address: http://www.showmeai.tech/article-detail/79Notice: All Rights Reserved. Please contact the platform and the author for reprint and indicate the source1.Python dictionaryA dictionary is another variable container model and can store objects of any type.Ea ...

Training a Classifier We learned how to define the neural network, calculate the loss and update the network weight What about data? Usually, when you have to deal with images, text, audio or video, you can use a standard python package that can load data into a numpy array, and then convert the array to torch* Tensor Image: pilot, opencvAu ...

fork someone else's project and fill it out again. My code is as follows https://gitee.com/fakerlove/machine-learning/tree/master/code Code source link 1. Wu Enda machine learning course - Assignment 1 - linear regression Reference link https://blog.csdn.net/qq_20412595/article/details/82181855 Definition and classification of regre ...

Series index: Chapter 1 Python Basics (1) Python Libraries - numpy, matplotlib Here is an example to understand the use of two important Python libraries. import numpy as np import matplotlib.pyplot as plt x = np.arange(0, 6, 0.1) y1 = np.sin(x) y2 = np.cos(x) plt.plot(x, y1, label="sin") plt.plot(x, y2, linestyle="--", label ...

[source code analysis] NVIDIA HugeCTR, GPU version parameter server - (4) 0x00 summary In this series, we introduce HugeCTR, an industry-oriented recommendation system training framework, which is optimized for large-scale CTR models with model parallel embedding and data parallel intensive networks. This paper mainly introduces the firs ...

1, Common skills in transfer learning: fine tuning 1.1 concept Take the weights trained on the big data set as the initialization weight of the specific task (small data set), and retrain the network (modify the full connection layer output as needed); The training methods can be: 1. Fine tune all layers; 2. Fix the weights of the front l ...

catalogue 1, Converter and estimator 2, Classification algorithm K-nearest neighbor algorithm Case code: Model selection and tuning Case code: Naive Bayesian algorithm: Summary of naive Bayesian algorithm Case code: Decision tree summary: Case code: Use random forest to achieve: Random forest summary summary Code set of this ca ...

preface: from torch.utils.data import Dataset from torch.utils.data import DataLoader import torchvision.transforms as transforms 1. Dataset in torch utils. data 2. It is required for loading text or image data sets, custom data sets, special formats or official data sets. DataLoader in 3,torch.utils.data uses this package for both text a ...