标签： 松江大学城快餐服务

The peak turns around! The new brother of the Football Association emerged, not Gao Hongbo Sun Wen, and went back or died a natural death.

As we all know, Du Zhaocai and Chen Xueyuan, two important officials of China Football Association, have been arrested and investigated since the football anti-corruption campaign began. In addition to the investigation of these two main players, many people involved are also related to the Football Association, and almost all of them are the heads of key departments within the Football Association. The General Administration of Sports has sent a working group to take charge of the Football Association, but fans hope that the Football Association will be replaced as soon as possible.

Who will be the next new president of the Football Association has really attracted the attention of fans. Recently, Li Xuan, a member of the Football Association, posted a message on social media, believing that this indicates that the change of the Football Association is officially put on the agenda. A football association will be established soon.

According to some media reports, some new members have appeared among the members of the State Sports General Administration. From the Provincial Sports Bureau to the State Sports General Administration, are you ready to take over the China Football Association? Maybe only the sports bureau knows about it.

However, Li Xuan, a media person, issued the latest statement saying that he didn’t know who would be in charge of the affairs of the Football Association, although some officials of the local sports bureau may have arrived in Beijing Paddy recently. Obey the boss’s orders. The next new team of the Football Association is also expected to follow the original path and appoint the deputy director of the General Administration of Sports.

Who is the new president of the Football Association? There is no way to study it now. In the end, only when the head of the Football Association is determined at the level of the State Sports General Administration can the change of the Football Association proceed smoothly. Therefore, analyzing the current situation, the new coach of the Football Association may not be a member of the current temporary team.

They, including Gao Hongbo and Sun Yat-sen, the current vice-presidents of FFA, are likely to gradually fade out of the stage of China football after the FFA team is re-elected. Of course, we don’t want the Football Association to stagger, and we don’t want the head of the Football Association to die easily. We want to select personnel. Track.

Infrastructure for training AI to solve common problems

In order to train artificial intelligence models that can solve common problems, infrastructure is needed to provide support. These infrastructures are usually composed of hardware, software and tools to improve the efficiency and accuracy of model training. This article will introduce the infrastructure for training AI to solve common problems.

I. Hardware infrastructure

When training artificial intelligence models, it is usually necessary to use high-performance computing hardware to provide support. The following are several common hardware infrastructures:

  1. CPU: The central processing unit (CPU) is a general-purpose computing hardware, which can be used to run various types of software, including artificial intelligence models. Although the performance of CPU is relatively low, it is still useful in training small models or debugging.

  2. GPU: A graphics processor is a special computing hardware, which is usually used to process images and videos. Because of its highly parallel structure, GPU can provide higher computing performance than CPU when training artificial intelligence models, so it is widely used.

  3. TPU: Tensor processor is a kind of hardware specially used for artificial intelligence computing, developed by Google. The performance of TPU is higher than that of GPU, and it is suitable for large-scale artificial intelligence model training and reasoning.

Second, the software infrastructure

In addition to hardware infrastructure, some software tools are needed to support the training of artificial intelligence model. The following are some common software infrastructures:

  1. Operating system: Artificial intelligence models usually need to run on an operating system, such as Linux, Windows or macOS.

  2. Development environment: Development environment usually includes programming language, editor and integrated development environment (IDE) for writing and testing artificial intelligence models. Common development environments include Python, TensorFlow, PyTorch and Jupyter Notebook.

  3. Frames and libraries: Frames and libraries provide some common artificial intelligence model algorithms and data processing tools, making model development and training more convenient. Common frameworks and libraries include TensorFlow, PyTorch, Keras and Scikit-Learn.

Third, the tool infrastructure

In addition to the hardware and software infrastructure, some tools are needed to support the training of artificial intelligence models. The following are several common tool infrastructures:

Dataset tool: Dataset tool is used to process and prepare training datasets, such as data cleaning, preprocessing, format conversion, etc. Common data set tools include Pandas, NumPy and SciPy.

2 Visualization tools: Visualization tools are used to visualize the training process and results to help users better understand the performance and behavior of the model. Common visualization tools include Matplotlib, Seaborn and Plotly.

Automatic parameter tuning tool: The automatic parameter tuning tool is used to optimize the parameters of the model to improve the performance and accuracy of the model. Common automatic parameter tuning tools include Optuna, Hyperopt and GridSearchCV.

In short, training artificial intelligence models to solve common problems requires the use of a variety of infrastructures, including hardware, software and tools. These infrastructures are designed to improve the efficiency and accuracy of model training, so that the model can better solve various practical problems. In practical application, users need to choose the appropriate infrastructure according to specific requirements and data characteristics, and design and implement it accordingly.