harshnagoriya
An ambitious computer science graduate student with diverse knowledge in Cloud Computing, Software Design, and various emerging technologies.
Seattle, WA, USA
Pinned Repositories
BigMart-Sales-Prediction
BigMart sales dataset consists of 2013 sales data for 1559 products across 10 different outlets in different cities. The goal of the following project is to build a regression model to predict the sales of each of 1559 products for the following year in each of the 10 different BigMart outlets. The BigMart sales dataset also consists of certain attributes for each product and store. This model helps BigMart understand the properties of products and stores that play an important role in increasing their overall sales. Proudly created by Harsh Nagoriya
Compiler-Design
A compiler translates the code written in one language to some other language without changing the meaning of the program. It is also expected that a compiler should make the target code efficient and optimized in terms of time and space. Compiler design principles provide an in-depth view of translation and optimization process. Compiler design covers basic translation mechanism and error detection & recovery. It includes lexical, syntax, and semantic analysis as front end, and code generation and optimization as back-end.
ComplaintManagementSystem
Covid19TimelineAnalysis
Face-Recognition-as-a-Service
Face-Recognition-on-a-PAAS
Face-Recognition-using-RaspberryPi
FaceMask-Detection-System
Gujarati-Character-Recognition
This project done by Harsh Nagoriya classifies printed or digitized Gujarati characters. Gujarati belongs to the genre of Devanagri scripts from the Indian subcontinent. The sample and test images for the characters were obtained from digital images available on the Internet and from scanned images of printed Gujarati text. For their classification, Convolutional neural netwrok classifiers were used with relu and softmax activations. Accuracy of the classifier and identifier is found to be around 99.63%.
Sales-Forecasting-using-Walmart-Dataset
Walmart data-set has sales data for 98 products across 45 outlets. The data-set contains sales per store, per department on weekly basis. The goal of this machine learning project is to forecast sales for each department in each outlet to help them make better data driven decisions for channel optimization and inventory planning. This project is proudly created by Harsh Nagoriya
harshnagoriya's Repositories
harshnagoriya/Compiler-Design
A compiler translates the code written in one language to some other language without changing the meaning of the program. It is also expected that a compiler should make the target code efficient and optimized in terms of time and space. Compiler design principles provide an in-depth view of translation and optimization process. Compiler design covers basic translation mechanism and error detection & recovery. It includes lexical, syntax, and semantic analysis as front end, and code generation and optimization as back-end.
harshnagoriya/Sales-Forecasting-using-Walmart-Dataset
Walmart data-set has sales data for 98 products across 45 outlets. The data-set contains sales per store, per department on weekly basis. The goal of this machine learning project is to forecast sales for each department in each outlet to help them make better data driven decisions for channel optimization and inventory planning. This project is proudly created by Harsh Nagoriya
harshnagoriya/BigMart-Sales-Prediction
BigMart sales dataset consists of 2013 sales data for 1559 products across 10 different outlets in different cities. The goal of the following project is to build a regression model to predict the sales of each of 1559 products for the following year in each of the 10 different BigMart outlets. The BigMart sales dataset also consists of certain attributes for each product and store. This model helps BigMart understand the properties of products and stores that play an important role in increasing their overall sales. Proudly created by Harsh Nagoriya
harshnagoriya/ComplaintManagementSystem
harshnagoriya/Covid19TimelineAnalysis
harshnagoriya/Face-Recognition-as-a-Service
harshnagoriya/Face-Recognition-on-a-PAAS
harshnagoriya/Face-Recognition-using-RaspberryPi
harshnagoriya/FaceMask-Detection-System
harshnagoriya/Gujarati-Character-Recognition
This project done by Harsh Nagoriya classifies printed or digitized Gujarati characters. Gujarati belongs to the genre of Devanagri scripts from the Indian subcontinent. The sample and test images for the characters were obtained from digital images available on the Internet and from scanned images of printed Gujarati text. For their classification, Convolutional neural netwrok classifiers were used with relu and softmax activations. Accuracy of the classifier and identifier is found to be around 99.63%.
harshnagoriya/hand-written-digit-recognition
Recognition of Handwritten Digit using Convolutional Neural Network, Python and Tensorflow
harshnagoriya/harshnagoriya
harshnagoriya/harshnagoriya.github.io
harshnagoriya/Hotspot-Analysis-on-Geo-Spatial-Data-using-Getis-Ord-Statistic
harshnagoriya/Housing-Price-Prediction
House prices increase every year, so there is a need for a system to predict house prices in the future. House price prediction can help the developer determine the selling price of a house and can help the customer to arrange the right time to purchase a house. There are three factors that influence the price of a house which include physical conditions, concept and location. This project aims to predict house prices. Proudly created by Harsh Nagoriya
harshnagoriya/Iris-flowers-classification
The aim of this project is to classify iris flowers among three species (setosa, versicolor or virginica) from measurements of length and width of sepals and petals.
harshnagoriya/Live-Helmet-Detection
harshnagoriya/Machine-Learning-Concepts
harshnagoriya/Movie-Recommendation-using-ML
Recommender System is a system that seeks to predict or filter preferences according to the user’s choices. Recommender systems are utilized in a variety of areas including movies, music, news, books, research articles, search queries, social tags, and products in general.The main goal of this machine learning project is to build a recommendation engine that recommends movies to users.
harshnagoriya/Operational-and-Strategic-decision-making-on-Geospatial-data
harshnagoriya/Pygames-Pong-game
In the following project, I have created a pong game using python library pygames. Pong is a table tennis-like game featuring simple two-dimensional graphics, The player controls an in-game paddle by moving it vertically across the left or right side of the screen.
harshnagoriya/Pygames-Snake-Game
In the following project, I have created a snake game using python library pygames. The following game is a same game which we used to play in our childhood in nokia phones. 😃
harshnagoriya/Wine-Quality-Prediction
It’s a known fact that older the wine, better the taste. However, there are several factors other than age that go into wine quality certification which include physiochemical tests like alcohol quantity, fixed acidity, volatile acidity, determination of density, pH and more. The main goal of this machine learning project is to build a machine learning model to predict the quality of wines by exploring their various chemical properties. Wine quality dataset consists of 4898 observations with 11 independent and 1 dependent variable.