Handwritten Digit Recognition using neural nets and ML classifiers
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Updated
Jan 24, 2019 - Python
Handwritten Digit Recognition using neural nets and ML classifiers
The purpose of the Sign-Interfaced Machine Operating Network, or SIMON, is to develop a machine learning classifier that translates a discrete set of ASL sign language presentations from images of a hand into a response from another system.
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ML pipeline to generate the predictions for the Driven Data competition.
This repo consists of data visualization project done for wealth management dataset from Kaggle. I have used various Machine Learning classifiers to calculate accuracy and precision to determine which model works best for this dataset. The agenda of this project is to analyze the trend of customer churn from a wealth management company.
Tumor prediction from microarray data using 10 machine learning classifiers. Feature extraction from microarray data using various feature extraction algorithms.
Décimo projeto de machine learning, dessa vez como foco em NLP para análise de sentimentos de posts do twitter.
A Set of Machine Learning Classifiers For RNA Containing Complexes
2022년 2학기 팀 프로젝트 : 도금공정 데이터 셋 분석(k-인공지능 제조데이터 분석 경진대회)
Minor project for disease prediction using machine learning classifiers such as logistic regression, decision tree, random forest, and MLP (Multi-layer Perceptron). The project focuses on evaluating the performance of these classifiers based on accuracy, confusion matrices, and classification reports.
A Simplilearn class project practicing machine learning classification algorithms.
This project focuses on the detection of myocardial infarction (heart attack) using machine learning techniques. We leverage the PTB diagnostic database, a widely used dataset in the field of cardiology.
To preform image classification on Rice Leaf Disease images using CNN via various methods.
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