Understanding LSTM for Mathematical Competitions

Understanding LSTM for Mathematical Competitions

Importance of Neural Networks in Mathematical Competitions In mathematical competitions, neural networks have gradually become a powerful assistant for participants due to their strong data processing and pattern recognition capabilities. Especially when dealing with complex, nonlinear, high-dimensional data, neural networks perform exceptionally well. They not only help us solve basic problems such as classification and … Read more

How to Quickly Use BERT?

How to Quickly Use BERT?

Follow the public account “ML_NLP“ Set as “Starred“, important content delivered first! Source | Zhihu Address | https://zhuanlan.zhihu.com/p/112235454 Author | TotoroWang Editor | Machine Learning Algorithms and Natural Language Processing Public Account This article has been authorized by the author and is prohibited from secondary reproduction Introduction Since I have been working on BERT models … Read more

Introduction to NLP: Tips on Knowledge Graphs and Learning NLP

Introduction to NLP: Tips on Knowledge Graphs and Learning NLP

Recently, I have received many letters from readers, most of whom are just starting to explore the fields of knowledge graphs and natural language processing, and the unfamiliarity brings some insecurity, leaving them feeling a bit lost. Therefore, taking this opportunity, this article discusses the topic of “How to Get Started with Knowledge Graphs and … Read more

Squat Detector Based on OpenCV and TensorFlow

Squat Detector Based on OpenCV and TensorFlow

Click on the above“Beginner Learning Vision” to select Star or “Pin” Important content delivered immediately This issue we will introduce how to use OpenCV and TensorFlow to implement squat detection. During the quarantine period, our physical activities are very limited, which is not good. When doing some home exercises, we must always maintain a high … Read more

Deep Learning Environment Setup Guide for RTX 3090: Pytorch, TensorFlow, Keras

Deep Learning Environment Setup Guide for RTX 3090: Pytorch, TensorFlow, Keras

Click on the above“Beginner Learning Vision” to add it to your favorites or “pin” Important content delivered to you first Author丨Yukyin@Zhihu Source丨https://zhuanlan.zhihu.com/p/279401802 This article is for academic sharing only. If there is any infringement, please contact us to delete the article. Introduction This article introduces the detailed process and code for setting up a deep … Read more

Comparing Images for Similarity Using Siamese Networks, Keras, and TensorFlow

Comparing Images for Similarity Using Siamese Networks, Keras, and TensorFlow

Author: Adrian Rosebrock Translator: Zhang Yiran Proofreader: wwl This article is about3700 words, recommended reading time8 minutes. In this article, you will learn how to use siamese networks and the deep learning libraries Keras / TensorFlow to compare the similarity of two images (and whether they belong to the same or different classes). This blog … Read more

Building a 3D-CNN in TensorFlow

Building a 3D-CNN in TensorFlow

Click on the above “3D Vision Workshop“, select “Star” Delivering valuable content promptly Author | Pan Duoduo Source | Deep Learning and Computer Vision Introduction to 3D-CNN The MNIST dataset classification is considered the hello world program in the field of computer vision. The MNIST dataset helps beginners understand the concept and implementation of Convolutional … Read more

The Ongoing Battle Between TF 2.0 and PyTorch: Current Situation

The Ongoing Battle Between TF 2.0 and PyTorch: Current Situation

Author | Jeff Hale Translator | Jackey Editor | Jane Produced by | AI Technology Camp (id: rgznai100) 【Introduction】 After the release of TensorFlow 2.0 and PyTorch 1.0, the discussion about which of the two is superior has been ongoing and still lacks a definitive conclusion. In this article, the author analyzes data from multiple … Read more

TensorFlow Tutorial: Quick Start to Deep Learning in 5 Steps

TensorFlow Tutorial: Quick Start to Deep Learning in 5 Steps

Authorized by AI Technology Camp (ID: rgznai100) Author: Liu Ziying This article is about 1300 words, recommended reading 6 minutes. This article teaches you how to develop deep learning models using 5 steps + 4 basic elements + 9 basic layer structures. As a programmer, we can learn deep learning model development just like learning … Read more

Advanced Tutorial for TensorFlow 2

Advanced Tutorial for TensorFlow 2

Remember when TensorFlow 2.0 was first released? A lot of developers were complaining: The official documentation was hard to find, bugs were not fixed and updated in a timely manner, and so on. Despite being online for so long, many developers still refuse to upgrade from 1.x or migrate from other frameworks. In fact, TensorFlow … Read more