we took nearly 100000 teacher details for training and a small amount of them for testing where we used 1 for least recommended and 5 for most recommended as output for training data.

This project predicts the "Scariest Monster" using a dataset of 12 million entries and 106 features. Utilizing GPU-accelerated processing and the Random Forest Regressor using the Nvidia Rapids API. The goal is to minimize RMSE for accurate predictions

Honors Thesis Research

This is a Phishing Classifier project in which model identify the phishing data using various machine learning techniques and help to prevent from malicious virus and cyber attack.

Códigos PYTHON. Pandas, Scikit-Learning, Rapids, Cuml, Cudf.

Compare feature importances created between cuml and sklearn RandomForestClassifiers

A compilation of various ML and DL models and ways to optimize the their inferences.

GPU-based ML to classify Higgs boson signal from background in particle physics using RAPIDS framework

Running KNN algorithm much faster on GPU for free using RAPIDS packages like cuML and cuDF

Proposed and implemented the NLP model to compute the semantic similarity between two english sentences/questions using the Support Vector Machine(SVM).

26th place solution from 3290 teams held on HackerEarth

Rapidsai_Machine_learnring_on_GPU

combination of EvalML with Rapids for the WiDS 2021 competition

Building NVIDIA's RAPIDS (cuDF, cuML...) in Arch Linux

The Incredible RAPIDS: a curated list of tutorials, papers, projects, communities and more relating to RAPIDS.