roshanr11

allstate-insurance-claims

Capstone project for Udacity's Machine Learning Engineer Nanodegree and a submission to Kaggle's Allstate Severity Claims competition.

bike-sharing-ml

In this project, I build, train, validate, and test a neural network from scratch using the popular Bike-Sharing dataset to predict daily bike rental ridership.

cmu_afs_tutorial

A user-friendly tutorial to acquaint CMU students to the Andrew File System.

Deep-Learning-for-Trading-RNN-LSTMs-getRichWithStocks.py

A predictive platform for stock market prediction, utilizing shallow machine learning algorithms built from scratch such as SLR and MSLR, as well as deep learning methods such as LSTMs + RNNs built with Keras.

image-captioning

Used deep learning to train a CNN + RNN/LSTM on the MS-COCO dataset to automatically generate captions.

ml-aws-sagemaker-deployment

ml-gan-faces

NLP-Machine-Translation

RL-Teaching-A-Quadcopter-To-Fly

roshanr11/cmu_afs_tutorial

A user-friendly tutorial to acquaint CMU students to the Andrew File System.

roshanr11/RL-Teaching-A-Quadcopter-To-Fly

roshanr11/NLP-Machine-Translation

roshanr11/customersegmentsv1

roshanr11/Dermatologist-AI-metrics

roshanr11/DNN-Speech-Recognizer

roshanr11/github-recitation

This repository is the base repository that students will fork and use for the git / github recitation

roshanr11/GitPractice

roshanr11/habitat-challenge

Code for the habitat challenge

roshanr11/KISS_Sanskrit_Parsing_Data

Dataset and evaluation script used for depednency parsing in Sanskrit

roshanr11/Mayan-EDMS

Fork of Mayan: Free Open Source Document Management System, for use in CMU 17-313

roshanr11/ml-customer-segments

roshanr11/ml-customer-segments-proj

roshanr11/ml-pca

roshanr11/ml-titanic

roshanr11/new_grad

A new lightweight auto-differentation library that directly builds on numpy. Used as a homework for CMU 11785/11685/11485.

roshanr11/NLP-Hidden-Markov-Model-POS-Tagger

roshanr11/Objectron

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

roshanr11/pytorch-image-models

PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MixNet, MobileNet-V3/V2, MNASNet, Single-Path NAS, FBNet, and more

roshanr11/Research-DCST

roshanr11/rl-blackjack-montecarlo

roshanr11/rl-deep-Q-learning

roshanr11/rl-frozen-lake

roshanr11/rl-taxi-scenario

roshanr11/rl-temporal-difference-methods

roshanr11/roshanr11

roshanr11/roshanr11.github.io

roshanr11/sentiment-rnn

roshanr11/The-Kaggle-Book

Code Repository for The Kaggle Book, Published by Packt Publishing

roshanr11/vision_transformer