My Machine Learning First Project on Github
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Updated
Jun 15, 2017 - Python
My Machine Learning First Project on Github
Diabetes Prediction Model Deployment
Used CDC dataset for heart attack detection in patients. Balanced the dataset using SMOTE and Borderline SMOTE and used feature selection and machine learning to create different models and compared them based on metrics such as F-1 score, ROC AUC, MCC, and accuracy.
To create a classification model to predict whether a person makes over $50k a year
Projeto de Machine learning - Classificação de texto NLTK, SpaCy e Sklearn
Comparision of classifiers
Supervised Machine Learning methods (Random Forest and SGD Classifier) to classify short conversations extracted from Reddit
Handwritten Digit Recognition using neural nets and ML classifiers
Detect heavy drinking episodes among individuals using accelerometer samples extracted from the individuals mobile devices.
Refining Fake News Classification with Sentiment Analysis. Final project for EMIS 8331: Advanced Data Mining at SMU (Spring 2017).
Python script that defines a Flask web application with two endpoints for predicting two machine learning models.
The code of the random forest project I shared on my Medium account
Diabetes Prediction using Machine Learning Algorithms
fraud_check_prj_10
BitVision is a Python-based computer vision app that allows users to record actions (3D poses) on video using Mediapipe and map them to keyboard inputs.
A tutorial for Kaggle's Titanic: Machine Learning from Disaster using Octave and Logistic Regression Modeling.
Classify problems - How to predict unbalanced data
An implementation of Random Forests in the Python programming language (accuracy tested with 100, 300, and 500 trees)
Web App to classify diaster reponse messages into response categories
This is a penguin species prediction web app
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