This project use mfcc feature extractor and Hidden Markove Model classification algorithm to recognition 0 - 9 digit of Kaggle dataset.
This code is written in python. To use it you will need:
Run python SDR.py
Multi-class confusion matrix library in Python
Interpretability methods applied on image classifiers trained on MNIST and CIFAR10
The goal of this project was to detect Diabetes using XGBoost based on the information of more than 70,000 patients through the questionnaire that they filled out for the Organization for Disease Control and Prevention.
Analysis of DNA Sequence Classification Using Neural Networks.
Classify Git commits with deep learning
We present our facial expression recognition models for fer-2013 dataset
دوره 12 ساعته یادگیری عمیق با چارچوب Keras
Classification Decision Trees