Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

ETL workflow and data analysis. ETL-workflow using prefect and pygrametl (SCD, slow changing dimension). Product classification based on product name.

Fast-API base StockSeer-API uses different machine learning alogs to forecast closing stock prices.

A modern GUI Based Face Recognition and Emotion Predictor using Machine Learning

Heart Disease Prediction using KNeighborsClassifier and RandomForestClassifier

KNeighborsClassifier for audio files

Learning with sklearn diabetes and iris flower dataset, single and multiple linear regression, classification with multi-layer perceptron, kneighbors and support vector machines.

Document Classification using Python and scikit-learn and nltk

A Machine Learning (ML) model that every ML beginner develops. This model is used to predict type of Iris flower based on the input.

This example application predicts the iris flowers classification based on the IRIS data set.

This module is limited to making use of the classifier KNeighborsClassifier from sklearn to apply it to the recognition of handwritten digits in the MNIST file, with a hit rate about 98,65% in test and extraordinary simplicity, especially compared to the complexity of classifiers based on neural networks. It also shows full sensitivity.

Esse pequeno projeto tem como objetivo fazer testes de acurácia com rede neural com apenas um neurônio sem classificadores e com 2 (dois) classificadores, sendo eles KNN e 1R.

This is a Smart Attendance System designed using a pre-trained model called Haar-Cascade Classifier, OpenCV and other various Dependencies to mark the attendance in a smarter way and saves the lecture time.

Python application using artificial intelligence using LaberEnconder, KNeighborsClassifier and RandomForestClassifier

Fruits Classification.

Comparision of classifiers

A simple machine learning program that use Scikit to predict gender based on the given data

The goal of this internship project was to create an educational program about artificial intelligence. This program is composed of activities and practical exercises. This repository contains the solutions of the main activities I created. During this project, I developed my knowledge of artificial intelligence and the Python language.

Realiza selecao de Beams com diferentes tecnicas