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Lesson 4.3 basic principle and manual implementation of gradient descent In the previous section, we have successfully constructed the loss function of logistic regression, but due to the particularity of the logistic regression model itself, we cannot adopt the calculation idea similar to SSE when constructing the loss function (at this time, ...

5.3 using pre trained convolutional neural networks Pre trained network: It has been used in large data sets (usually large-scale image classification tasks) Training Practice good , ...

preface The last article introduced pyg from the basic tools provided by pyg. However, we generally use the tripartite library as a building block to build a relatively large model and use it in our own data set, rather than being satisfied with the simple model and standard data set in the running demo. Therefore, this paper will reproduce T- ...

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 ...

Recently, I was burst by yolox. In addition, I have too many plots for yolo series. I tried yolof before. Now, yolox and openvino reasoning happen to need this part. Now I'll try to make a preliminary exploration. 1, Basic configuration cuda 10.1 2, Environment construction 1. Installing yolox git clone git@github.com:Megvii-BaseDetection/YOLO ...

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 ...

DenseNet, a densely connected convolution network with Pytorch Note32 A summary of all notes: Pytorch Note Happy Planet DenseNet Previous Resnet enhanced the information flow between the front and back layers through Shortcuts, alleviated the disappearance of gradients to some extent, and built the neural network very deeply. Furthermore ...

[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 ...

As an undergraduate majoring in artificial intelligence, I came into contact with face detection in my freshman study. And with the help of teachers, successfully use the code to recognize and train a series of face pictures. Now I want to share the problems and training results I encountered in the process of training the model. Face Detectio ...

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 ...