Use Deep Learning model to diagnose 14 pathologies on Chest X-Ray and use GradCAM Model Interpretation Method
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Updated
Oct 12, 2020 - Jupyter Notebook
Use Deep Learning model to diagnose 14 pathologies on Chest X-Ray and use GradCAM Model Interpretation Method
Deep Neural network using CNN pre-trained model to visually diagnose between 3 types of skin lesions
Evaluation of supervised predictions for two-class and multi-class classifiers
Machine-learning models to predict whether customers respond to a marketing campaign
Toolkit for Doing Research with ECMAScript-based Statistics (DRESS Kit)
Survival modelling using Cox proportional hazard regression model
The classification goal is to predict whether the client will subscribe (1/0) to a term deposit (variable y).
pyWitness performs data analyses and model fitting of recognition memory data, specifically eyewitness identification data.
Resample precision-recall curves correctly!
[Master Thesis 2017] Scripts for calculating metrics to assess performance of a drug design software.
Python code to obtain metrics like receiver operating characteristics (ROC) curve and area under the curve (AUC) from scratch without using in-built functions.
This project aims to predict the occurrence of diabetes using machine learning techniques. The dataset used for this analysis is the "diabetes_prediction_dataset.csv" file, which contains various features related to an individual's health condition.
These codes are written as a part of ECE219 Large Scale Data Mining course at UCLA.
Two-Dimensional Data Whitening and Receiver Operational Characteristic Determination
The repository contains the code for the various machine learning algorithms used to make a predictive analysis of tweets on GST in India
Wolfram Language (aka Mathematica) paclet for Receiver Operation Characteristic (ROC) functions.
Explore how certain hyperparameters and features in a logistic regression model affect image classification
Human Resources Analytics
Classification-Techniques-For-Fraud-Detection
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