AI比赛相关信息汇总
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Updated
Jan 26, 2023
AI比赛相关信息汇总
TextClf :基于Pytorch/Sklearn的文本分类框架,包括逻辑回归、SVM、TextCNN、TextRNN、TextRCNN、DRNN、DPCNN、Bert等多种模型,通过简单配置即可完成数据处理、模型训练、测试等过程。
A C4.5 tree classifier based on a zhangchiyu10/pyC45 repository, refactored to be compatible with the scikit-learn library.
Spam filtering module with Machine Learning using SVM (Support Vector Machines).
Open source malware detection program using machine learning algorithms on system call traces.
ML-powered news classifier: categorise articles via REST API. Built with scikit-learn, model comparison with VotingClassifier, and a REST API service for real-time predictions with Docker and Kubernetes deployment
文本分类,评论分类,朴素贝叶斯多分类,酒店评论分类
This is ML project which is based on Classification of Credit Score
Stat-gram is microservice tool for Business and Influencers on Instagram platform that uses AI to help with Marketing and Management.
Classification of MXenes into metals and non-metals based on physical properties
The code uses the scikit-learn machine learning library to train a decision tree on a small dataset of body metrics (height, width, and shoe size) labeled male or female. Then we can predict the gender of someone given a novel set of body metrics.
Failure prediction for APU’s on a Metro System Research project source code
Sentiment Analysis: approximating Word2Vec results with SPPMI-SVD
Heart Disease Analysis
This project involves the implementation of efficient and effective LinearSVC on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.
Sentiment analysis of a Tweets dataset by using machine learning algorithm. Datascience Final Project Jan 2022
In this repo, I am doing data analysis in water potability and check each and every classification model's accuracy.
A jupyter notebook for analyzing and estimating with sklearn a multiclass classification problem for the Machine Learning (DD2421) course
Training a classifier to differentiate between positive and negative movie review sentences in the "sentence polarity dataset v1.0"
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