Semantic Segmentation of CMR with a U-Net based architecture. Implemented in TF2.X. Trainings, prediction and evaluation scripts/notebooks for heatmap based right ventricle insertion point detection on cine CMR images. Koehler et al. 2022, BVM

Time series forecasting using ML models (ARIMA, SARIMA, SARIMAX and Prophet)

Library for computing classifier Learning Curves & iPython notebooks to improve your learning curve for using Learning Curves for ML research and practice!

This notebook describes how to compute and derive insights from various classification evaluation metrics.

If you want to learn these topics, i refer you to go through this notebook.

This repository contains a Jupyter Notebook exploring the adult income dataset. The notebook performs Exploratory Data Analysis (EDA), including visualizations with charts and graphs. Additionally, it implements various classification models to predict income and analyzes their accuracy.

This Jupyter notebook project evaluates the accuracy of language model responses to generated questions by comparing them to a ground truth dataset using cosine similarity and ROUGE metrics.

Contained in this repository are the Jupyter notebooks that contain the scripts used in this project. Examples include: exploratory data analysis, creation of training, validation and test data sets, and CNN model development and data extraction.