binaryclassification

A New, Interactive Approach to Learning Data Science

ML-powered Loan-Marketer Customer Filtering Engine

The goal of the project is to build a predictive model using machine learning concepts to predict customer attrition for a telecom service company.

DECISION TREE CLASSIFIER - HYPER PARAMETER TUNING - Binary Classification

Text Classification Problem : Wrote a module to classify Amazon-Product Reviews as favourable/unfavourable. Achieved accuracy of 78% and an F1 score of .81 using Logistic Regression on a test-train split of 20%, where total records were around 50000.

Submission for Kaggle Competition "Real or Not? NLP with Disaster Tweet" (Top 10%) using SVM's, LSTM's, and BERT

Binary Classification of mnist data using Stochastic Gradient Descent(SGD)

Binary classification and Multiclass classification with pipelining and parameter tuning with GridsearchCV and RandomizedSearchCV

Classifier using supervised machine learning algorithm which can accurately predict whether or not the patients in the dataset have diabetes.

The task here is to predict whether a bank currency note is authentic or not based on four attributes i.e. variance of the image wavelet transformed image, skewness, entropy, and curtosis of the image.

Benchmark of sci-kit learn models and a tensorflow model for Binary Image Classification

Can we predict how long a patient will be in a hospital with a fair comparison on gender, race and health service areas?

Project for my semester evaluation, course Artificial Intelligence.