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Abstract: the content of this article is my understanding in the process of learning Deep Learning, and the code is written by myself (the code ability is not very strong). If there is something wrong, you are welcome to point out and correct it. Why use convolutional neural network There are two problems when processing pictures using a ...

1, Preliminary work My environment: Locale: Python 3 six point fiveCompiler: Jupiter notebookDeep learning environment: tensorflow2 four point oneData address: [portal] Previous highlights: 100 cases of deep learning convolutional neural network (CNN) to realize mnist handwritten numeral recognition | day 1100 cases of deep learning - c ...

preface At present, with the popularity of artificial intelligence, it has attracted the attention of many industries to artificial intelligence. At the same time, it has also ushered in waves of artificial intelligence learning upsurge. Although the principles behind artificial intelligence can not be introduced in detail in a short artic ...

0x0. preface I answered the question about how to contribute to PyTorch before. See the original post: https://www.zhihu.com/question/502301777/answer/2248950419 . The answer mentioned that when some operators were developed in OneFlow last year, some bug s of PyTorch operators were found based on the operator AutoTest framework, and feedba ...

6.1 parameter update SGDMomentumAdaGradAdam 6.1.1 SGD Simple but possibly inefficient, e.g. f = 0.05x2+y2Gradient direction: may not point to the lowest pointLocal minimum and global minimum` import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import numpy as np def f(x,y): return np.power(x,2)/20 + np.power(y, ...

TensorRT accelerated application ⭐ tensorrtx Download TensorRT is a C + + version of deep learning architecture, which is parallel to tensorflow and pytorch. We want to deploy yolov5 to the development board with TensorRT, which is divided into two steps: 1 Install TensorRT, 2 Rewrite the network trained by each training framework with Tenso ...

One hot coding of category tensors by PyTorch This article has authorized the platform of the polar city and is the official account of the polar platform. No second reprint is allowed without permission Original document: https://www.yuque.com/lart/ugkv9f/src5w8 Code warehouse: https://github.com/lartpang/CodeForArticle/tree/main/OneHotEnco ...

Detailed explanation of BN core parameters of PyTorch Original document: https://www.yuque.com/lart/ugkv9f/qoatss affine Modify during initialization When fine is set to True, the BatchNorm layer will learn the parameters gamma and beta. Otherwise, these two variables are not included, and the variable names are weight and bias. .train() If af ...

Implementation of Computer Vision PyTorch (1) PyTorch Base Module Computer vision can be widely used in many real world fields. For example, basic image processing, image recognition, image segmentation, target tracking, image classification, attitude estimation, and so on. In-depth learning, many learning frameworks have been developed, such ...

Markov models are often used to analyze a large number of random events After a discrete event occurs, another discrete event will occur with a certain probability under the condition of the previous event. For example, we can establish a Markov model for a weather system: In this weather system model, if it is sunny today, there is 70% possib ...