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Introduction to LeNet neural network LeNet neural network was proposed by Yan LeCun, one of the three giants of deep learning. He is also the father of convolutional neural networks (CNN). LeNet is mainly used for handwritten character recognition and classification, and has been used in American banks. The implementation of LeNet establishes ...

background Advertising fraud is one of the important challenges that digital marketing needs to face. Click fraud will waste advertisers a lot of money and mislead click data. The competition provided about 500000 hits. Special attention: we simulated the data, hid the meaning of some features, and desensitized them. Please predict whether th ...

IoU IoU (Intersection over Union), also known as overlap / intersection union ratio. That is, the intersection/Union in the figure above. The code implementation is as follows: # one pre, one gt def IoU(pred_box, gt_box): ixmin = max(pred_box[0], gt_box[0]) iymin = max(pred_box[1], gt_box[1]) ixmax = min(pred_box[2], gt_box[2]) ...

1.VGG16 theory VGG is a convolutional neural network model proposed by Simonyan and Zisserman in the document very deep revolutionary networks for large scale image recognition. Its name comes from the abbreviation of the visual geometry group of Oxford University where the author works. The model participated in the ImageNet image classificat ...

Basic functions of processing tensors in 5 PyTorchEvery beginner of deep learning should know these five basic functions of pytoch.Being able to construct neural networks in an accurate and effective way is one of the most sought after skills of recruiters in deep learning engineers. PyTorch is a Python library mainly used for deep learning. On ...

Part of speech prediction by Python note42 LSTM Summary of all notes: Pytoch note Happy Planet Model introduction For a word, there will be different parts of speech. First, we can make a preliminary judgment according to the suffix of a word. For example, the suffix - ly is very likely to be an adverb. In addition, a same word can repre ...

This article continues with the last part. This article continues with examples of multi-catalog data training models. 4. Multi-directory data training This example is based on previous batch data training and repeated iteration training, and stores data files in multiple directories instead of just one directory to support distributed data a ...

In the first issue, we explained and realized the most basic linear regression. In this issue, we will talk about the regression problem to the classification problem. At this time, we need to add some elements based on the linear regression model, that is activation function so that our model can solve nonlinear data and classification pro ...

Realize the step-by-step deepening from manual derivation to automatic derivation and then to the model. Implementation of two-layer neural network with numpy A fully connected ReLU neural network, a hidden layer, no bias, L2 Loss (h is hidden layer, ReLU activation function): h ...

Serial article: Last Vernacular machine learning concepts 1, Machine learning category Machine learning can be divided into supervised learning, unsupervised learning, semi supervised learning and reinforcement learning according to the difference of learning data experience, that is, the difference of label information of training data. 1.1 ...