Webhook Webhook is a type of HTTP-based callback function that can be used for lightweight, event-driven communication between two Application Programming Interfaces (APIs). A client provides a server API with a unique URL and specifies the events it wants to be informed about. After setting up a webhook, the client no longer needs to poll the server; when the specified event occurs, the server will automatically send the relevant payload to the client’s Webhook URL. Webhooks can be an important component of automation and are easy to implement (just a single HTTP request that can be embedded anywhere). Webhook message pushing is supported by domestic platforms such as Feishu, DingTalk, and WeChat Work. The advantages are clear, but the downside is the lack of uniform parameters for HTTP requests, since it’s too simplistic without a standardized protocol. Different platforms use different terms, such as “msg” on one platform and “message” or “text” on another. Therefore, to fully utilize webhooks, it’s necessary to create your own Webhook parsing service, which thankfully isn’t complicated. This article will use Github Webhook as an example, parsing and pushing it to WeChat Work with Flask.

Background Information Bottom-tier 211 University, majoring in Big Data at the Computer Science Department, ranked (2/99), CET6 (553), three project experiences, no published papers, some minor awards; Summer Camps The basic situation of the summer camps can be seen in the following image: Of these, I entered 13 camps, excluding some that were just for promotional purposes and did not offer admission and the Chinese Academy of Sciences series (did not contact any professors), I participated in 5 summer camps in total. The experiences of these 5 camps are presented in a narrative manner below.

Background Very few themes manage to balance practicality and aesthetics. For example, although the aurora theme looks cool, it displays too little content on a single page, detracting from the focus on content; just want to tinker This led to the following requirements: A single configuration file generates multiple blog themes that coexist simultaneously. Consistent routing between sites, facilitating easy theme switching. Since the entire blog is now managed through Git, while it’s possible to use different branches to manage different themes, this approach is very inconvenient for updating articles. Therefore, this solution is not adopted. Configuration Since hexo generate can specify a configuration file, this provides a possibility for our solution. This time, we are using Hexo Next 8 and Aurora two sets of themes, with the configuration files organized as follows in the root directory:

Essay Questions (7*8 points) Discuss the relationship between data, graphics, and visualization. Discuss the visualization process. Discuss the characteristics of comparative graphs, distribution graphs, and process graphs. Discuss the characteristics of vector graphics and bitmap graphics. Discuss the characteristics of structured data, semi-structured data, and unstructured data. Discuss the classification of cloud services and the characteristics of Huawei Cloud DLV. Discuss the characteristics of AR VR MR. Read Graphs Write Code A graph with three lines, with legend, style review is limited to line type, point type (matplotlib).

Review class video recording GRC and his friends’ notes 0. Question Types Type Quantity Score Short Answer 4 60 Design 2 25 Unknown Type 1 15 The teacher was quite secretive about the last question, “As long as you listened in class, you could still score some points.” 1. Outline Chapter Two

1. Introduction Concept of Machine Learning The ability to equip machines with a skill without deterministic programming Performance Task Experience, the program has improved P over T using E, that is learning Divided by task types: regression, classification, clustering, dimensionality reduction Divided by learning methods: supervised, unsupervised, reinforcement learning 2. Model Evaluation and Selection Key section Various evaluation metrics, including writing code, calling library functions Example problems like covariance matrix, precision, confusion matrix, ROC curve Basic concepts like overfitting problem and solutions