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cpp-nanodegree

fresher-2021

patient_case_similarity

Calculation of Patient Similarity based on Patient Demographic and Case Details extracted from XML annotations, Electronic Health Record (EHR) Project for Grand Finale of Smart India Hackathon 2019 for the Problem statement by EzDI in which we made a system for assessment of similarity between patient using vector concatenation techniques and operations.

project_dog_breed_classifier

In this project, one can learn how to build a pipeline that can be used within a web or mobile app to process real-world, user-supplied images. Given an image of a dog, the algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.

project_plagiarism_detection.

In this project, I was tasked with building a plagiarism detector that examines a text file and performs binary classification; labelling that file as either plagiarized or not, depending on how similar that text file is to a provided source text. Detecting plagiarism is an active area of research; the task is non-trivial and the differences between paraphrased answers and original work are often not so obvious.

project_route_planner

Data Structures & Algorithms Nanodegree Udacity

project_route_planner_cpp_astar_algorithm

A course project in C++ using real map data and A* search to find a path between two points, just as you might see in a desktop or mobile mapping application. The project you written will be using data from the OpenStreetMap project.

project_system_monitor_project_cpp

A System Monitor Application similar to htop in various Linux variants.

project_unscramble_computer_science_problems

Unscramble Computer Science Problems

sentiment-analysis-model-deployment.

# SageMaker Deployment Project The notebook and Python files provided here, once completed, result in a simple web app which interacts with a deployed recurrent neural network performing sentiment analysis on movie reviews. This project assumes some familiarity with SageMaker, the mini-project, Sentiment Analysis using XGBoost, should provide enough background. Please see the [README](https://github.com/udacity/sagemaker-deployment/tree/master/README.md) in the root directory for instructions on setting up a SageMaker notebook and downloading the project files (as well as the other notebooks).

store_monitoring_system

A Store Monitoring System For Restaurants that generates report about their stores uptime and downtime

ucf101-classification