sklearn-classify

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。

Spam filtering module with Machine Learning using SVM (Support Vector Machines).

A C4.5 tree classifier based on a zhangchiyu10/pyC45 repository, refactored to be compatible with the scikit-learn library.

Open source malware detection program using machine learning algorithms on system call traces.

文本分类，评论分类，朴素贝叶斯多分类，酒店评论分类

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.

Stat-gram is microservice tool for Business and Influencers on Instagram platform that uses AI to help with Marketing and Management.

Sentiment Analysis: approximating Word2Vec results with SPPMI-SVD

Cat vs Dog Classification using SVM and KNN Classifiers of Sklearn Library

Loan Prediction Problem Analysis

In this repo, I am doing data analysis in water potability and check each and every classification model's accuracy.

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.

A Binary Classification Problem Optimized For AU-ROC Curve,. From Data Cleaning to Model Validation, Classifying whether a blight ticket will be paid in time or not, Trained 3 different Classifier on a Highly imbalanced Data provided by Detroit Open Data Portal with around 160000 Tickets.

Hyperparameter tuning using Sklearn Pipelines

试题分类 学习sklearn的练手项目

Classification of MXenes into metals and non-metals based on physical properties

An AI game in Python.

TP final de la materia 7550 - Introduccion a los sistemas inteligentes

Classification Project: Sonar rocks or mines

🏎️ Vehicle Detection Project using OpenCV and scikit-learn for the Self-Driving Car Nanodegree at Udacity

Implementing Logistic Regression to predict results and using the sklearn library from SVM to perform classification

NLP using Python, Sklearn, Decision Tree on Jupyter NoteBook

This is our seventh-level machine learning project, which analyze the students performance. The project started and ended at 2019.

sohu_news classification

Aim was to classify the provided data with different classifiers and compare their performance. 17 different classifiers were employed and their results are documented in a Jupyter notebook

Using Ml classifiers to train on a given set of data of diabetic pregnant women to predict whether their off-springs will inherit the diabetes or not.

Assignment & notes from CS677-Data Science with Python. Use stock prices and features (average daily return and volatility) as the required dataset and apply many basic classifier models and algorithms of data science in analysis.