kaizhang9751 Goto Github PK

bayesian-neural-networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace and more

bighouse

competition_baselines

docs

TensorFlow documentation

network_dos_attack_detection

Using the 1998 DARPA Intrusion Detection Evaluation dataset I configured a Random Forest model for anomaly detection

pedestrian-detection

Pedestrian detection using the TensorFlow Object Detection API. Includes multi GPU parallel processing inference.

pedestriandetectionsystem

Automatic pedestrian detection and monitoring system based on TensorFlow.基于TensorFlow的自动化行人检测（人体检测）和监控（视频监控）系统。

sms

:school: :mortar_board: 一个未使用框架的学生信息管理系统 : 项目概述全面，代码注释详细,逻辑结构清晰，非常适合作为初学 Java web 的同学的第一个练手项目啦 ~

studentachievementmanagementsystem

Java+SQLServer学生成绩管理系统（代码+数据库）

web_scraping_challenge

In this assignment, you will build a web application that scrapes various websites for data related to the Mission to Mars and displays the information in a single HTML page. The following outlines what you need to do. ### Before You Begin 1. Create a new repository for this project called `web-scraping-challenge`. **Do not add this homework to an existing repository**. 2. Clone the new repository to your computer. 3. Inside your local git repository, create a directory for the web scraping challenge. Use a folder name to correspond to the challenge: **Missions_to_Mars**. 4. Add your notebook files to this folder as well as your flask app. 5. Push the above changes to GitHub or GitLab. ## Step 1 - Scraping Complete your initial scraping using Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter. * Create a Jupyter Notebook file called `mission_to_mars.ipynb` and use this to complete all of your scraping and analysis tasks. The following outlines what you need to scrape. ### NASA Mars News * Scrape the [NASA Mars News Site](https://mars.nasa.gov/news/) and collect the latest News Title and Paragraph Text. Assign the text to variables that you can reference later.