LoRA E5,, stars:10, update:2024-05-08 23:28:37 (2024-05-09, Jupyter Notebook, 0KB, 下载0次)
http://www.pudn.com/Download/item/id/1715247492565669.html
沪深4107 A1
CSI4107 A1 (2024-02-12, Jupyter Notebook, 0KB, 下载0次)
A1 AIE22108 V1.ipynb版本
A1 AIE22108 V1.ipynb (2024-02-04, Jupyter Notebook, 0KB, 下载0次)
A1 AIE22105 V1.ipynb版本
A1 AIE22105 V1.ipynb (2024-02-04, Jupyter Notebook, 0KB, 下载0次)
CV A1边缘检测
CV A1 Edge Detection (2024-01-27, Jupyter Notebook, 0KB, 下载0次)
bf intorg YOLOv8开发
bf intorg YOLOv8 dev (2024-01-19, Jupyter Notebook, 0KB, 下载0次)
本项目是参加飞桨常规赛:中文场景文字识别的项目,项目score为85.94141。 生成的预测文件为work中的result.txt文件 项目任务为识别包含中文文字的街景图片,准确识别图片中的文字 本项目源于[https: aistudio.baidu.com aistud...](https: aistudio.baidu.com aistudio projectdetail 615795%EF%BC%8C%E5%9C%A8%E6%AD%A4%E5%9F%BA%E7%A1%80%E4%B8%8A%E8%BF%9B%E8%A1%8C%E4%BF%AE%E6%94%B9)
This project is to participate in the flying oar regular race: Chinese scene character recognition project, and the project score is 85.94141. The generated prediction file is the result.txt file in the work. The project task is to identify the street view pictures containing Chinese characters, and accurately identify the characters in the pictures. This project originates from [https: aistudio.baidu.com aistud...] (https: aistudio.baidu.com aistudio projectdetail 615795% EF% BC% 8C% E5% 9C% A8% E6% AD% A4% E5% 9F% BA% E7% A1% 80% E4% B8% 8A% E8% BF% 9B% E8% A1% 8C% E4% BF% AE% E6% 94% B9) (2023-12-11, Jupyter Notebook, 0KB, 下载0次)
A1.支持向量机，，
A1.Support Vector Machines,, (2023-09-24, Jupyter Notebook, 0KB, 下载0次)
在Connect4环境上端到端实现AlphaZero。，
An end-to-end implementation of AlphaZero on a Connect4 environment., (2023-09-13, Jupyter Notebook, 0KB, 下载0次)
练习使用谷歌可乐和GitHub教室，
Practice using Google colab and GitHub classroom, (2023-08-19, Jupyter Notebook, 0KB, 下载0次)
参考
Refer to
对[https: github.com NCAR intake-esm- datastore tree master catalogs中部分json文件做了路径的修改](https: github.com NCAR intake- esm- datastore tree master catalogs%E4%B8%AD%E9%83%A8%E5%88%86json%E6%96%87%E4%BB%B6%E5%81%9A%E4%BA%86%E8%B7%AF%E5%BE%84%E7%9A%84%E4%BF%AE%E6%94%B9),
[https: github.com NCAR intake esm datastore tree master catalogs] (https: github.com NCAR intake esm datastore tree master catalogs% E4% B8% AD% E9% 83% A8% E5% 88% 86json% E6% 96% 87% E4% BB% B6% E5% 81% 9A% E4% BA% 86% E8% B7% AF% E5% BE% 84% E7% 9A% 84% E4% BF% AE% E6% 94% B9), (2020-08-02, Jupyter Notebook, 0KB, 下载0次)
The code is followed the instruction by https://leemeng.tw/attack_on_bert_transfer_learning_in_nlp.html#%E7%94%A8-BERT-fine-tune-%E4%B8%8B%E6%B8%B8%E4%BB%BB%E5%8B%99,stars:1, update:2022-01-09 16:55:37
The code is followed the instruction by <a href="https://leemeng.tw/attack_on_bert_transfer_learning_in_nlp.html#%E7%94%A8-BERT- fine-tune-%E4%B8%8B%E6%B8%B8%E4%BB%BB%E5%8B%99" rel="nofollow">https://leemeng.tw/attack_on_bert_transfer_learning_in_nlp.html#%E7%94%A8-BER...</a> , stars:1, update:2022-01-09 16:55:37 (2023-06-25, Jupyter Notebook, 10KB, 下载0次)
利用Python进行数据分析([https: read.douban.com reader ebook 15249337 )源代码整理版](https: read.douban.com reader ebook 15249337 %EF%BC%89%E6%BA%90%E4%BB%A3%E7%A0%81%E6%95%B4%E7%90%86%E7%89%88)
Data analysis using Python ([https: read.douban.com reader ebook 15249337) source code collation) (https: read.douban.com reader ebook 15249337% EF% BC% 89% E6% BA% 90% E4% BB% A3% E7% A0% 81% E6% 95% B4% E7% 90% 86% E7% 89% 88) (2018-12-31, Jupyter Notebook, 35601KB, 下载0次)
Dive into Deep Learning中文第二版公开课目前已经开课,详情可去[http: courses.d2l.ai zh-v2 查询。本项目用于配合此次公开课,使用libtorch和C++语言练习公开课上的例子。](http: courses.d2l.ai zh-v2 %E6%9F%A5%E8%AF%A2%E3%80%82%E6%9C%AC%E9%A1%B9%E7%9B%AE%E7%94%A8%E4%BA%8E%E9%85%8D%E5%90%88%E6%AD%A4%E6%AC%A1%E5%85%AC%E5%BC%80%E8%AF%BE%EF%BC%8C%E4%BD%BF%E7%94%A8libtorch%E5%92%8CC++%E8%AF%AD%E8%A8%80%E7%BB%83%E4%B9%A0%E5%85%AC%E5%BC%80%E8%AF%BE%E4%B8%8A%E7%9A%84%E4%BE%8B%E5%AD%90%E3%80%82)
Dive into Deep Learning Chinese version 2 open class has started, For details, please go to [http: courses. d2l. ai zh-v2 to query. This project is used to practice the examples in this open class with libtorch and C++language.] (http: courses. d2l. ai zh-v2% E6% 9F% A5% E8% AF% A2% E3% 80% 82% E6% 9C% AC% E9% A1% B9% E7% 9B% AE% E7% 94% A8% E4% BA% 8E% E9% 85% 8D% E5% 90% 88% E6% AD% A4% E6% AC% A1% E5% 85% AC% E5% BC% 80% E8% AF% BE% EF% BC% 8C% E4% BD% BF% E7% 94% A8libtor ch% E5% 92% 8CC++% E8% AF% AD% E8% A8% 80% E7% BB% 83% E4% B9% A0% E5% 85% AC% E5% BC% 80% E8% AF% BE% E4% B8% 8A% E7% 9A% 84% E4% BE% 8B% E5% AD% 90% E3% 80% 82) (2021-05-25, Jupyter Notebook, 42515KB, 下载0次)
数据512 A1:_Data_curation
Data 512 A1:_Data_curation (2019-10-17, Jupyter Notebook, 962KB, 下载0次)
, and matplotlib. 该项目基于2019年纽约市Airbnb开放数据,数据来源于[https: www.kaggle.com datasets dgomonov new- york-city-airbnb-open-dat...](https: www.kaggle.com datasets dgomonov new-york- city-airbnb-open- data%E3%80%82%E4%BD%BF%E7%94%A8%E5%B7%A5%E5%85%B7%E4%B8%BAJupyter)
, and matplotlib This project is based on the 2019 Airbnb Open Data in New York City, sourced from [https: www.kaggle.com datasets dgomonov new york city airbnb open dat...] (https: www.kaggle.com datasets dgomonov new york city airbnb open data% E3% 80% 82% E4% BD% BF% E7% 94% A8% E5% B7% A5% E5% 85% B7% E4% B8% BAJupyter) (2023-05-06, Jupyter Notebook, 507KB, 下载0次)
NLP_wuenda,吴恩达老师在2020年6月份推出了NLP课程,网址如下:[https: www.deeplearning.ai natural-language- processing- specialization 。本人忙里偷闲将老师的视频和作业都完...](https: www.deeplearning.ai natural- language-processing- specialization %E3%80%82%E6%9C%AC%E4%BA%BA%E5%BF%99%E9%87%8C%E5%81%B7%E9%97%B2%E5%B0%86%E8%80%81%E5%B8%88%E7%9A%84%E8%A7%86%E9%A2%91%E5%92%8C%E4%BD%9C%E4%B8%9A%E9%83%BD%E5%AE%8C%E6%88%90%E4%BA%86%EF%BC%8C%E5%90%8E%E7%BB%AD%E4%BC%9A%E6%8C%81%E7%BB%AD%E6%9B%B4%E6%96%B0%E8%AF%BE%E7%A8%8B%E7%9A%84%E8%B5%84%E6%96%99%E5%92%8C%E4%BD%9C%E4%B8%9A%E3%80%82)
NLP_ Wuenda, teacher Andrew Y. Ng launched the NLP course in June 2020, The website is as follows: [https: www.deeplearning. ai natural language - processing - specialization. I took a break from my busy schedule to finish the teacher s videos and assignments...] (https: www.deeplearning.ai natural- language-processing- specialization %E3%80%82%E6%9C%AC%E4%BA%BA%E5%BF%99%E9%87%8C%E5%81%B7%E9%97%B2%E5%B0%86%E8%80%81%E5%B8%88%E7%9A%84%E8%A7%86%E9%A2%91%E5%92%8C%E4%BD%9C%E4%B8%9A%E9%83%BD%E5%AE%8C%E6%88%90%E4%BA%86%EF%BC%8C%E5%90%8E%E7%BB%AD%E4%BC%9A%E6%8C%81%E7%BB%AD%E6%9B%B4%E6%96%B0%E8%AF%BE%E7%A8%8B%E7%9A%84%E8%B5%84%E6%96%99%E5%92%8C%E4%BD%9C%E4%B8%9A% E3%80%82) (2021-01-08, Jupyter Notebook, 399552KB, 下载0次)
这个notebook是根据去年o2o比赛冠军的代码（[https://github.com/wepe/O2O-Coupon-Usage-
Forecast）整理注释的，使用notebook（安装了插件方便整理）,加了一些自己的注释，调了bug，实测可以跑通。用xgboost应该在0.795左右。](https://github.com/wepe/O2O-Coupon-
Usage-
Forecast%EF%BC%89%E6%95%B4%E7%90%86%E6%B3%A8%E9%87%8A%E7%9A%84%EF%BC%8C%E4%BD%BF%E7%94%A8notebook%EF%BC%88%E5%AE%89%E8%A3%85%E4%BA%86%E6%8F%92%E4%BB%B6%E6%96%B9%E4%BE%BF%E6%95%B4%E7%90%86%EF%BC%89,%E5%8A%A0%E4%BA%86%E4%B8%80%E4%BA%9B%E8%87%AA%E5%B7%B1%E7%9A%84%E6%B3%A8%E9%87%8A%EF%BC%8C%E8%B0%83%E4%BA%86bug%EF%BC%8C%E5%AE%9E%E6%B5%8B%E5%8F%AF%E4%BB%A5%E8%B7%91%E9%80%9A%E3%80%82%E7%94%A8xgboost%E5%BA%94%E8%AF%A5%E5%9C%A80.795%E5%B7%A6%E5%8F%B3%E3%80%82)
,
This notebook was compiled based on the code from last year s O2O competition champion (https: github. com wepe O2O Coupon Usage - Forecast). It was annotated using the notebook (with plugins installed for ease of compilation), added some own comments, fixed bugs, and tested to run smoothly. Using xgboost should be around 0.795 (https: github.com wepe O2O-Coupon- Usage- Forecast%EF%BC%89%E6%95%B4%E7%90%86%E6%B3%A8%E9%87%8A%E7%9A%84%EF%BC%8C%E4%BD%BF%E7%94%A8notebook%EF%BC%88%E5%AE%89%E8%A3%85%E4%BA%86%E6%8F%92%E4%BB%B6%E6%96%B9%E4%BE%BF%E6%95%B4%E7%90%86%EF%BC%89,%E5%8A%A0%E4%BA%86%E4%B8%80%E4%BA%9B%E8%87%AA%E5%B7%B1%E7%9A%84%E6%B3%A8%E9%87%8A%EF%BC%8C%E8%B0%83%E4%BA%86bug%EF%BC%8C%E5%AE%9E%E6%B5%8B%E5%8F%AF%E4%BB%A5%E 8%B7%91%E9%80%9A%E3%80%82%E7%94%A8xgboost%E5%BA%94%E8%AF%A5%E5%9C%A80.795%E5%B7%A6%E5%8F%B3%E3%80%82) (2018-08-09, Jupyter Notebook, 15KB, 下载0次)