Source: ZHUAN ZHI This article introduces a book and suggests a 5-minute read. After reading this book, you will understand the mathematical foundations and concepts of deep learning, and be able to build new deep learning applications using the demonstrated prototypes. This book is built on the foundation of the first edition, updating chapters and … Read more
Overview Understand the state-of-the-art transformer models. Learn how we implement transformers for the image captioning problem we have seen using TensorFlow. Compare the results of transformers with attention models. Introduction We have seen that the attention mechanism has become a compelling component of various tasks (such as image captioning) in sequence modeling and transduction models, … Read more
Introduction Creating precise machine learning models capable of identifying and locating multiple objects in a single image remains a core challenge in computer vision. However, with recent advancements in deep learning, object detection applications are easier to develop than ever before. The TensorFlow Object Detection API is an open-source framework built on top of TensorFlow … Read more
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
What is Scikit-learn? Scikit-learn is an open-source Python library that includes various unsupervised and supervised learning techniques. It is built on technologies and libraries such as Matplotlib, Pandas, and NumPy, which help simplify coding tasks. Features of Scikit-learn include: Classification (including K-Nearest Neighbors) Preprocessing (including Min-Max normalization) Clustering (including K-Means++ and K-Means) Regression (including Logistic … Read more
Click on the “Beginner’s Visual Learning” above to select “Star” or “Pin“ Important content delivered promptly 0. Introduction During the pandemic, we searched for TensorFlow pre-trained models on GitHub and found a repository containing 25 object detection pre-trained models with their performance and speed metrics. Utilizing one of these models to build a social distance … Read more
Click the above“Mechanical and Electronic Engineering Technology” to follow us To install TensorFlow in PyCharm on Windows 10 (for Python 3.9 version), you can follow the steps below: Open PyCharm and create a new Python project or open an existing project. In the top menu bar of PyCharm, select “File” -> “Settings”. In the pop-up … Read more
The Telecom Business Hall APP, as the entry-level application for China Telecom’s online services, has allowed its development team to have close contact with TensorFlow and artificial intelligence (AI) technology. AI is an area that the Telecom Business Hall APP had never explored before, and even the engineers involved in the project transitioned from Android … Read more
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
Source: ZHUAN ZHI This article serves as a tutorial and is recommended for a 5-minute read. This tutorial's practical section will be based on TF-GNN, a library for handling graph-structured data in TensorFlow. Graphs are universal data structures that can represent information from various domains (social, biomedical, online transactions, etc.). Graph Neural Networks (GNNs) are … Read more