Author: Adrian Rosebrock Translated by: Wu Zhendong Proofread by: Zhang Damin This article is about 8000 words, and it is recommended to read for 10+minutes. This article will tell you how to use image-based adversarial attacks to disrupt deep learning models, leveraging the Keras and TensorFlow deep learning libraries to implement your own adversarial attacks.[ … Read more
Author: Chen ZhiyanThis article is about 3500 words, and it is recommended to read in 5 minutes This article introduces several very useful deep learning frameworks, their advantages and applications. By comparing each framework, developers can learn how to selectively use them to efficiently and quickly complete project tasks. For beginners in data science, using … Read more
Author | Rohan Jagtap Compiled by | ronghuaiyang Source | AI Park TensorFlow 2.x provides a lot of simplicity in building models and overall use of TensorFlow. In this article, we will explore 10 features of TF 2.0 that make using TensorFlow smoother, reduce the number of lines of code, and improve efficiency. TensorFlow 2.x … Read more
Source: Algorithm Advancement This article is about 3000 words long and is recommended to be read in 8 minutes. This article will help everyone understand some concepts that may be confusing during the learning process. Nowadays, after becoming proficient in using specialized frameworks and high-level libraries like Keras、TensorFlow or PyTorch , we no longer have … Read more
In the process of constructing the detailed model structure of the twin neural network, we first create a shared convolutional network. We have already understood the convolutional layer, pooling layer, and fully connected layer. First, please understand the following concepts: Convolutional Layer Pooling Layer Convolutional Layer Fully Connected Layer Shared Convolutional Layer Euclidean Distance Let’s … Read more
Neural Networks (NN) are an important branch of machine learning and have been widely applied in various fields such as image recognition, natural language processing, and speech recognition. With the support of R, the implementation of neural networks has become easier, allowing developers to use various libraries to implement, train, and tune neural network models. … Read more
Tong Ling from A Fei Temple Quantum Bit Production | WeChat Official Account QbitAI PhD student Nathan Hubens from Télécom SudParis encountered some difficulties while training a CNN. During experiments using the VGG16 model trained on the CIFAR10 dataset, he performed 50 iterations and found that the model did not learn anything. It can be … Read more
Selected from Hackernoon Author: Debarko De Translated by Machine Heart Contributors:Li Shimeng, Lu This article briefly introduces what recurrent neural networks are and their operating principles, and provides an example implementation of an RNN. What are recurrent neural networks (RNNs)? How do they work? Where can they be used? This article attempts to answer these … Read more
Author: Pulkit Sharma Translator: Chen Zhiyan Proofreader: Ding Nanya This article contains about 3900 words, and is recommended to read for 10+ minutes. This article analyzes and compares the advantages and applications of five very useful deep learning frameworks. Overview Since I started my career, I have always been a programmer. I enjoy coding from … Read more
Click on the above “Beginner’s Visual Learning” to choose to add “star” or “top” Important content delivered promptly For students learning data science, implementing a neural network from scratch can help you understand many interesting concepts. However, I do not think it is wise to build deep learning models on real datasets unless you have … Read more