Ubuntu 22.04 Configuring ROS2 Humble
This article is a detailed tutorial on how to configure ROS2 Humble on Ubuntu 22.04 system, including virtual machine installation, environment configuration, network setup, software source replacement, and ROS1 and ROS2 installation steps.

SpringBoot + MinIO to achieve file slicing and uploading at very high speeds
In modern Internet applications, file uploading is a common and important function. However, with the increase in file size, traditional file uploading methods often face problems such as inefficiency and time-consuming. In order to improve the speed and efficiency of large file uploads, we can use file slicing upload technology and combine SpringBoot and MinIO to realize this function.

DataWorks operation error collection of SQL lines of code is too long to generate errors, how to solve the problem
DataWorks is a one-stop big data development and governance platform provided by Aliyun, which supports the whole process of data processing, such as data integration, data development, data services, data quality management, data security management and so on. In the process of using DataWorks, you may encounter various operation errors. The following are some common error reporting situations and their possible causes and solutions.

2.8 Training and Optimization of Handwriting Digit Recognition
This article discusses how to improve the real-world results of models in handwritten digit recognition tasks through debugging and optimization during model training, including methods such as calculating classification accuracies, checking the model training process, incorporating calibrations or tests to evaluate model effectiveness, avoiding overfitting, and using visual analysis tools.

2.9 Recovery training for handwriting digit recognition
This article describes how to implement the resumption of training of a handwritten digit recognition model in the Flying Paddle (PaddlePaddle) framework, including the saving and loading of the model parameters and the optimizer state, to ensure that the training process can continue from the last saved state after an interruption.

4.3.2 Image Classification ResNet in Action: Eye Recognition - Model Construction
This article describes how to use the ResNet50 model in the Flying Paddle framework for eye recognition in practice, achieving about 96% accuracy on the validation set with 5 epochs of training, and provides a detailed code implementation of model construction, training, evaluation, and prediction.
