Android app which will help patients with Alzheimer and dementia

Scripts for machine learning algorithms in MATLAB/Octave and python

It is Based on Anamoly Detection and by Using Deep Learning Model SOM which is an Unsupervised Learning Method to find patterns followed by the fraudsters.

Credit card fraud detection

Anamoly Detection for Detecting Defected Manufactured Semi-Conductors, as in this case of Classification, the Defected Chips would be very less in comparison to perfect Chips so we have apply either Over-Sampling or Under-Sampling.

Detecting Frauds in Online Transactions using Anamoly Detection Techniques Such as Over Sampling and Under-Sampling as the ratio of Frauds is less than 0.00005 thus, simply applying Classification Algorithm may result in Overfitting

This is an highly imbalanced data with only 1.72% minority and 98.28% majority class, i will be explaining Up and down sampling and effect of sampling before and while doing cross validation. Model has been evaluated using precision recall curve.

Machine Learning from Stanford University (Andrew Ng) - Assignments and Lectures

Finding the doctors who are taking unethical use of their insurance funds

The official repository of TeamGabru.

Showing outliers and novelty detection in a datasets, from Scikit-learn

Application to recover a realtime AWS Dynamodb table data without losing newly added data to resolve damages from spam attacks and accidental data deletions

This Project is detect outliers in sensor networks. We are using ISSNIP Single hop dataset for this.

Detect Fraud Transaction from the dataset . The project involves dealing with unbalanced dataset and concept drift. I have implemented 4 machine learning algorithms to predict Fraud Transaction . These are - Logistic Regression ,Support Vector Machine(SVM), Local Outlier Factor(LOF) and isolation Tree.See my python 3 notebook to get more insight…

My solutions for the ML course assignment provided by Coursera.

The customer delivery data of a restaurant is explored to detect anomalies which are then rectified by replacing errors and imputing missing values.

MS Project under Dr. Grace Wang.