binary-classifier

Use Python and NLTK to build out your own text classifiers and solve common NLP problems

The uploaded codes help to classify emails into spam and non spam classes by using Support Vector Machine classifier.

Build intelligent applications that can interpret the human language to deliver impactful results

Silicon Valley inspired binary classifier to identify hot-dogs and not-hot-dogs. Source: https://www.youtube.com/watch?v=vIci3C4JkL0

Access the Linear or RBF kernel SVM from OCaml using the R e1071 or svmpath packages

An image classifier that determines whether an image contains a dog or a cat.

Diabetes Prediction using Three Machine Learning Algorithms - Logistic Regression, Random Forest & SVM

This repository contains some machine learning projects as a practise on machine learning course on Coursera for Prof. Andrew Ng from Stanford University.

Short project done for the course "Introduction to Machine Learning" @ UniTS.

The primary objective of this project was to develop a predictive model capable of accurately determining whether a bank customer will maintain or close their account. Kaggle Playground Series S4E1

In this we trained a model to detect if there is a tumor in the brain image given to the model. Meaning a model for binary class with an accuracy of above 90 for same and cross validation.

Pipeline for mask detection over a Pi camera video feed.

A binary classifier to test whether an image belongs to the "hot dog" class or the "not hot dog" class, as seen on HBO's Silicon Valley.

Binary Linear Classifier - AI Supervised Algorithm

Binary classifier that determines whether an image is of a cat or a dog.

Explores classification methods to predict whether a student will answer a test question correctly

Online Passive Aggressive Binary Classifier

MNIST Handwritten Digits Classification

A novel ML-based binary classifier to tell viral and non-viral long reads apart in metagenomic samples.

Binary classification model using PyTorch to predict heart failure using clinical data.