pat922's Stars
hankcs/HanLP
中文分词 词性标注 命名实体识别 依存句法分析 成分句法分析 语义依存分析 语义角色标注 指代消解 风格转换 语义相似度 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理
zxing/zxing
ZXing ("Zebra Crossing") barcode scanning library for Java, Android
academic/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
bingoogolapple/BGAQRCode-Android
QRCode 扫描二维码、扫描条形码、相册获取图片后识别、生成带 Logo 二维码、支持微博微信 QQ 二维码扫描样式
yuzhiqiang1993/zxing
基于zxing的扫一扫,优化了扫描二维码速度,集成最新版本的jar包(zxing-core.jar 3.3.3),集成简单,速度快,可配置颜色,还有闪光灯,解析二维码图片,生成二维码等功能
bradtraversy/devconnector_2.0
Social network for developers, built on the MERN stack
javedsha/text-classification
Machine Learning and NLP: Text Classification using python, scikit-learn and NLTK
liu-nlper/DocumentClassification
This code implements a simple CNN model for document classification with tensorflow.
saidziani/Arabic-News-Article-Classification
Automatic categorization of documents, consists in assigning a category to a text based on the information it contains. We'll follow different approach of Supervised Machine Learning.
techleadhd/todolist-ios
Sample todolist app iOS application with IGListKit, Yoga Layout, Material Design.
kirkmicz/Cheat-Sheet
yangysc/Document-Classification
Classify documents using Python based on SVM and TF-IDF.
Arghyadeep/Document-Classification-with-CNN
h00s/chatgpt-telegram-bot
This is a Telegram bot that uses ChatGPT to generate responses to messages.
baurine/study-note
Record study notes
irfanelahi-ds/document-classification-python
How to classify documents into a set of pre-defined classes using Python sklearn, NLTK and by applying machine learning algorithms (Naive Bayes, Random Forest, SVM)
andreacanepa/NaiveBayes-Text-Classification
Naive Bayes algorithm for multi-category text classification.
imsagargoyal/TextClassification
Document classification or document categorization is a problem in Information science, computer science and arts. The task is to assign a document to at least one or a lot of categories. this could be done "manually" (or "intellectually") or algorithimically, and also the documents to be classified could also be texts, images, music, etc. every quite document possesses its special classification issues. Documents could also be classified consistent with their subjects or consistent with different attributes (such as document kind, author, printing year etc.). This project can specialize in algorithmic strategies, precisely machine learning algorithms that area unit wide employed in IP and computing. There area unit several classification algorithms akin to Naive Bayes, Decision Tree and etc, all of that have their advantages and downsides. There area unit several public text knowledge set on-line for classification, here, I will be able to apply classification algorithms more on notable 20_newsgroup knowledge set from UCI Machine Learning Repository, that features a assortment of twenty thousand messages, collected from twenty completely different web news newsgroups. The news are classified consistent with their contents.
PriyanshuKhandelwal/Document-categorization-Binary-Classification-
Using document sets of two different categories and will try to classify them based on the content they hold. We will be using both Naive Bayes, Support Vector Machines and Random Forest algorithm for this classification.