本报告是我作为UTD 2024年安永数据科学挑战的一部分所做工作的成果。挑战是预测给定位置是否存在水稻作物。这一挑战将考虑来自欧洲哥白尼（哨兵-1和哨兵-2）计划和美国宇航局陆地卫星计划的卫星数据。
This repo is the result of my work as part of the EY Data Science Challenge 2024 at UTD. The challenge is to predict the presence, or non-presence, of rice crops at a given location. This challenge will consider satellite data from the European Copernicus (Sentinel-1 and Sentinel-2) program and from NASA s Landsat program. (2024-05-17, Jupyter Notebook, 0KB, 下载0次)
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Byte written test, Tencent written test, Ali written test, Meituan written test, Pinduoduo written test, Ant Financial Service written test, Baidu written test, Netease written test, Huawei written test, Glory written test, oppo written test, Xiaomi written test, Xiaohongshu written test, Bilibili written test, Mihayou written test, Ctrip written test, Kuaihou written test, Dajiang written test, Didi written test, Dawu written test, iFLYTEK written test, SHEIN written test, China Merchants Bank written test, Shenxinfu written test, UFIDA written test, Shunfeng written test, WeBank written test, Qianxin written test, Lenovo written test Test, 58 local written test, Tucson Future written test, Futu written test, Qunari written test, Weilai written test, eggplant science and technology written test, ape coaching written test and other Internet giants, developed and algorithm written test (2024-05-10, Jupyter Notebook, 0KB, 下载0次)
以數位工具輔助汽車租賃業者的ESG決策!只要求基本的車輛資料(引擎大小、汽缸數、車重)便能迅速產出客製化淘汰清單,將有效地簡化決策流程、精簡人力、結省資料收集時間。
Use digital tools to assist the ESG decision-making of car rental operators! Only basic vehicle information (engine size, cylinder number, vehicle weight) is required to quickly produce customized elimination list, which will effectively simplify decision-making process, simplify manpower, and save data collection time. (2024-03-25, Jupyter Notebook, 0KB, 下载0次)
该存储库包含一个机器学习项目，专注于预测泰坦尼克号上乘客的生存。该项目使用sklearn库中的支持向量回归（SVR）模型，涉及数据预处理和预测。
This repository contains a machine learning project focused on predicting the survival of passengers on the Titanic. The project uses a Support Vector Regression (SVR) model from the sklearn library and involves data preprocessing and prediction. (2024-01-07, Jupyter Notebook, 0KB, 下载0次)
在这个项目中，我们将使用Airflow创建一个数据管道。该管道将下载播客片段，并使用语音识别自动转录它们。我们将结果存储在可以轻松查询的SQLite数据库中。
In this project, we ll create a data pipeline using Airflow. The pipeline will download podcast episodes and automatically transcribe them using speech recognition. We ll store our results in a SQLite database that we can easily query. (2023-12-31, Jupyter Notebook, 0KB, 下载0次)
该存储库包含一个数据科学项目，专注于预测泰坦尼克号上乘客在悲惨灾难中的生存。目标是建立一个机器学习模型，该模型可以基于各种特征，如社会经济地位、年龄、性别等，准确预测乘客是否幸存。
This repository contains a data science project that focuses on predicting the survival of passengers aboard the Titanic during the tragic disaster. The goal is to build a machine learning model that can accurately predict whether a passenger survived or not based on various features such as socio-economic status, age, gender, and more. (2023-08-09, Jupyter Notebook, 0KB, 下载0次)
因为在极客时间上面学习了陈旸老师的数据分析实战45讲,发现里面还差了一些细节的东西,所以开了这个仓库重新对其中的部分章节进行回炉重整,希望对各位入门数据分析的有帮助。
Since I learned 45 lectures on data analysis from Mr. Chen Yang during the geek time, I found that there were still some details missing, so I opened this warehouse to review some of the chapters, hoping to help you get started with data analysis. (2020-04-18, Jupyter Notebook, 581KB, 下载0次)
该项目有关大数据的分类问题,是根据用户信息提取不同的特征,然后监督学习用户的分类,总共有5类,正常用户、客服人员、快递员、骚扰电话
The classification of big data in this project is to extract different features according to user information, and then supervise and learn the classification of users. There are five categories in total, namely normal users, customer service personnel, courier, and harassing calls (2020-03-06, Jupyter Notebook, 99228KB, 下载0次)
Skin-Clothes-Hair-Segmentation-using-SMP,3クラス(肌、服、髪)のセマンティックセク?メンテーションを実施するモテ?ル(A model that performs semantic segmentation of 3 classes(skin, clothes, hair))
Skin Lothes Hair Segmentation Using SMP, 3 クラススセマンィックセク?メン?ションをソるモ A model that performs semantic segmentation of 3 classes (skin, clothes, hair) (2021-12-20, Jupyter Notebook, 79845KB, 下载0次)