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Airam - PU8ASR / PX8C1730 / PP8004SWL's Projects

alahid icon alahid

Script para transformar o Arduino Uno em interface HID

avl icon avl

Árvore Binária (Auto-Balanceada) de Busca

cancer-bayes icon cancer-bayes

Predicting breast cancer at 97.51% accuracy with Naive Bayes Classifier for learning purposes.

classesmd5-64 icon classesmd5-64

Extract classes.dex from apk and returns base64 MD5 raw encoded

dump1090 icon dump1090

Dump1090 is a simple Mode S decoder for RTLSDR devices

hx711 icon hx711

An Arduino library to interface the Avia Semiconductor HX711 24-Bit Analog-to-Digital Converter (ADC) for Weight Scales.

naive_bayes icon naive_bayes

Naive Bayes implementation with digit recognition sample

naive_bayes_retweet icon naive_bayes_retweet

A (set of) Python scripts to retrieve tweets (for a given query) and RT one with highest score from Naïve Bayes classifier.

naivebayes icon naivebayes

A multilabel Naive Bayes classifier for HTML documents

naivenayes icon naivenayes

Implements Naive Bayes algorithm to classify movie reviews as positive or negative.

pacman-ai icon pacman-ai

PacMan Machine Learning Artificial Intelligence Project

rfid icon rfid

Arduino RFID Library for MFRC522

spam-filter icon spam-filter

A python program to classify the text content as spam or not-spam just like the email classification, Using the Naive bayes classifier the content files are classified. This is part of Machining Learning !!!

svxlink icon svxlink

Advanced repeater system software with EchoLink support for Linux including a GUI, Qtel - the Qt EchoLink client

tweet-sentiment-classifier icon tweet-sentiment-classifier

Tweet Sentiment Classifier is a program built in Python that uses Data Mining concepts like Naive Bayes Classification to classify the tweets into positive, negative, neutral or mixed sentiments. The input data is the 2012 presidential election (between Obama and Romney) tweets. This training set consists of about 7000 tweets for each Obama and Romney and the test set consists of about 2500 tweets. The program learns from the training set and applies the classification on the test set and generates the Accuracy, Precision, Recall, F-Score and Confusion Matrix.

welcomescreen icon welcomescreen

Create & design a splash screen with animation from Up to Down

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