用于数据集maelstrom-a1的climetlab的数据集插件，
A dataset plugin for climetlab for the dataset maelstrom-a1, (2023-10-18, Jupyter Notebook, 0KB, 下载0次)
以%97的准确性检测52000篇假新闻，
Detecting Fake News with 52,000 article with %97 Accuracy, (2020-02-01, Jupyter Notebook, 0KB, 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)
使用TensorFlow 2.0检测枪击的音频分类深度学习模型。测试集准确率97.5%，跟踪率99%...
Audio classification deep learning model using TensorFlow 2.0 to detect Gunshots. 97.5% test set accuracy and 99% training set accuracy was achieved on Binary-Urban8K. This work was done during my summer internship at TUKL-NUST lab. (2020-02-16, Jupyter Notebook, 3842KB, 下载0次)
您的新闻文章、博客、YouTube视频、学习材料、维基百科内容等的全合一摘要。
An All-in-1 summarizer for your news articles, blogs, YouTube videos, study materials, Wikipedia content, etc. (2022-10-25, Jupyter Notebook, 180KB, 下载0次)
用于预测给定查询的基于Django的Web应用程序属于哪种语言，即R、java、javascript、PHP...
A Django Based Web App for predicting a given query belongs to which language i.e R , java , javascript , PHP , python . The model is trained using LSTM s with a training accuracy of 97% and testing accuracy of 80%. The data that the model is trained with queries collected from a dataset in Kaggle originally extracted from StackOverflow. (2020-09-19, Jupyter Notebook, 23356KB, 下载0次)
2019年大创项目和2019年新苗人才计划项目,针对翻拍的图片进行检测与识别,主要使用lbp算法,前期准确率在80.08%左右,后不断扩大优化图片数据库,准确率提升到97.4%结题。
The 2019 Da Chuang project and the 2019 New Miao Talent Plan project mainly used the lbp algorithm for detection and recognition of remastered images, with an initial accuracy rate of around 80.08%. Later, they continuously expanded and optimized the image database, and the accuracy rate improved to 97.4%. (2021-03-03, Jupyter Notebook, 162342KB, 下载0次)
高效的基于基因表达（微阵列数据）和ML-DL算法的准确分类方法...
Here, we describe the comparison of the most used algorithms in classical ML and DL to classify carcinogenic tumors described on 11_tumor data base, obtaining accuracies between 76.97% and 100% for tumor identification. Our results bring up a more efficient an accurate classification method based on gene expression (microarray data) and ML/DL (2020-04-13, Jupyter Notebook, 4487KB, 下载0次)
用bevy_mujoco实现Unitree A1机器人神经网络行走的实例
An example project using bevy_mujoco to make Unitree A1 Robot walk with neural network (2023-03-20, Jupyter Notebook, 41756KB, 下载0次)
Raspberry Pi上的SLAM机器人定位与RP LIDAR A1集成。点云远程可视化为我们做...
Robotic Localization with SLAM on Raspberry Pi integrated with RP LIDAR A1. Point Cloud remote visualization doing using MQTT in real-time. (2023-03-15, Jupyter Notebook, 17276KB, 下载0次)
...划时代，并实现了97.38%的测试准确率，优于支持向量机等传统分类器...
Galaxy classification system helps astronomers with the method of grouping galaxies as per their visual form. The foremost notable being the Hubble sequence, which is considered one among the foremost used schemes in galaxy morphological classification. The Edwin Powell Hubble sequence was created by Hubble in 1926. In this project, Galaxy (2018-09-27, Jupyter Notebook, 7951KB, 下载0次)
本科生小组项目，我们使用TCN-CNN构建了一个心电图分类器，准确率为97%
Undergraduate group project in which we built an ECG classifier using a TCN- CNN with 97% accuracy (2021-10-02, Jupyter Notebook, 27553KB, 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)
猫狗分类烧瓶应用程序，我们通过实现卷积神经网络（CNN）来对狗进行分类，成功地建立了一个深度神经网络模型...
We successfully built a deep neural network model by implementing Convolutional Neural Network (CNN) to classify dog and cat images with very high accuracy 97.32 %. In addition, we also built a Flask application so user can upload their images and classify easily. (2021-03-25, Jupyter Notebook, 12567KB, 下载0次)
使用陀螺仪和加速度计变量的神经网络人类活动识别，验证精度在KAGGLE上最好。人工神经网络具有97.98%的验证准确率和预测精度...
The VALIDATION ACCURACY is BEST on KAGGLE. Artificial Neural Network with a validation accuracy of 97.98 % and a precision of 95% was achieved from the data to learn (as a cellphone attached on the waist) to recognise the type of activity that the user is doing. The dataset s description goes like this: The sensor signals (accelerometer and (2018-10-02, Jupyter Notebook, 1174KB, 下载0次)
道路裂缝检测神经网络-，一种使用keras构建的卷积神经网络，用于检测道路裂缝，准确率为97.5%。
Road-Cracks-Detection-Neural-Network-,A convolutional neural network built using keras to detect cracks on road with 97.5% accuracy. (2021-01-07, Jupyter Notebook, 408KB, 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)
A1关于网络抓取Pandas数据科学，在python中使用Pandas学习网络抓取。-数据科学，
Learning WebScraping using Pandas in python. - Data Science
, (2021-12-02, Jupyter Notebook, 795KB, 下载0次)
这是免费代码营文章“如何构建准确率超过97%的图像分类器”的回购。分类器使用Python、PyTorch、Numpy、Matplotlib、Seaborn、JSON和PIL。
This is the repo for the Free Code Camp article, "How to build an image
classifier with greater than 97% accuracy." Classifier utilizes Python,
PyTorch, Numpy, Matplotlib, Seaborn, JSON, and PIL.
, (2019-02-17, Jupyter Notebook, 1800KB, 下载0次)