Big Data Digest authorized reprint from Data Pai THU Author: Aravind Pai Translation: Wang Weili, Zhang Yihao In our programming journey, we always turn to the most advanced architectures. Thanks to deep learning frameworks such as PyTorch, Keras, and TensorFlow, implementing advanced architectures has become easier. These deep learning frameworks provide a simple way to … Read more
Produced by Big Data Digest Compiled by: Hong Yingfei, Ning Jing PyTorch, one of the deep learning framework libraries, is an open-source deep learning platform from Facebook that provides seamless transition from research prototypes to production deployment. This article aims to introduce the basics of PyTorch, helping beginners write initial Python PyTorch code in 4 … Read more
Click below on thecard to follow the “Beginner’s Guide to Python” public account Let’s discuss some techniques that help you conduct experiments during the training process. I will provide some theory, code snippets, and complete workflow examples. The main points include: Dataset Splitting Metrics Reproducibility Configuration, Logging, and Visualization Dataset Splitting I prefer a split … Read more
Pytorch-Lightning: A Simplified Framework for Python Deep Learning! Pytorch-Lightning is a lightweight framework based on PyTorch, specifically designed to simplify the training process of deep learning models. It abstracts common coding patterns, allowing you to focus on building models without getting bogged down in cumbersome details. Today, we’ll discuss the basic usage of this framework … Read more
A beginner in CV, I write this article to help other novices like me understand how to easily learn and allow experts to reinforce their basics (manual dog head), feel free to leave any questions in the comment section for discussion~ 1. Overview Paper: Densely Connected Convolutional NetworksPaper link: https://arxiv.org/pdf/1608.06993.pdf As the Best Paper at … Read more
Click the “Beginner’s Visual Learning” above to choose to add “Star” or “Pinned“. Important content delivered promptly. From a high-level perspective of our deep learning project, we have prepared the data, and now we are ready to build our model. Prepare Data Build Model Train Model Analyze Model Results When we talk about the model, … Read more
Hello everyone, I am Redstone! In the previous article: Implementing VGGNet (Theoretical Part) We detailed the network structure of VGGNet. Today, we will use PyTorch to reproduce the VGGNet network and apply the VGGNet model to solve a classic Kaggle image recognition competition problem. Let’s get started! 1. Dataset Preparation In the paper, the authors … Read more
Evolution of CNN Architecture: From AlexNet to ResNet Hello everyone, I am Sister Liu. Today we will delve into the evolution of Convolutional Neural Networks (CNN), which is one of the most important technological developments in the field of computer vision. Background Knowledge Before the rise of deep learning, traditional image recognition methods relied on … Read more
The hands-on deep learning live course has completed the first three parts! In the past 4 months, Dr. Mu Li, a senior chief scientist at Amazon has explained the basics of deep learning, convolutional neural networks, and computer vision. Since the course started, over 10,000 people have participated in the live learning, and the course … Read more
Produced by Big Data Digest Source: eisenjulian Compiled by: Zhou Jiale, Qian Tianpei Using deep learning libraries like TensorFlow and PyTorch to write a neural network is no longer a novelty. But do you know how to elegantly build a neural network using Python and NumPy? Nowadays, there are many deep learning frameworks available, equipped … Read more