地球资源数据云——数据资源详情

语言检测人工智能软件

发布时间：2026-03-17 15:40:41资源ID：2033810726102405121资源类型：免费

该数据集《Language Detect Artificial Intelligence Software》主要用于监督学习任务，数据形态以图像为主，应用场景偏向文本内容分析。 题目说明：Language Detection Artificial Intelligence Software - By Emirhan BULUT - NLP AI 任务类型：图像监督学习。 建议流程：先检查类别分布与脏样本，再用迁移学习（如 ResNet/EfficientNet）建立基线。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：language_detection.csv。 I developed 'Language Detection Artificial Intelligence Software'. I share this software with all humanity for free from Kaggle and GitHub. It is an NLP system. The sensitivity score is quite high and the accuracy score is in a very advantageous position. It has 97% accuracy and 98.4% sensitivity score. I share Dataset and Artificial Intelligence Software as open source. I used the Naive Bayes algorithm and manipulated the dataset to improve the algorithm. In this way, the sensitivity rate and score of the software has been increased. In addition, I adapted the data according to the algorithm and made the algorithm work. In this study, it was studied on the data, not on the algorithm. I wish conveniences, Emirhan BULUT

语言检测人工智能软件

摘要概览

该数据集《Language Detect Artificial Intelligence Software》主要用于监督学习任务，数据形态以图像为主，应用场景偏向文本内容分析。 题目说明：Language Detection Artificial Intelligence Software - By Emirhan BULUT - NLP AI

任务类型：图像监督学习。

建议流程：先检查类别分布与脏样本，再用迁移学习（如 ResNet/EfficientNet）建立基线。

评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。

可用文件：language_detection.csv。

I developed 'Language Detection Artificial Intelligence Software'. I share this software with all humanity for free from Kaggle and GitHub. It is an NLP system. The sensitivity score is quite high and the accuracy score is in a very advantageous position. It has 97% accuracy and 98.4% sensitivity score.

I share Dataset and Artificial Intelligence Software as open source. I used the Naive Bayes algorithm and manipulated the dataset to improve the algorithm. In this way, the sensitivity rate and score of the software has been increased. In addition, I adapted the data according to the algorithm and made the algorithm work.

In this study, it was studied on the data, not on the algorithm.

I wish conveniences,

Emirhan BULUT