rakeshchary2511 Goto Github PK
Name: Rakesh Chary Bangaroj
Type: User
Company: University of Houston - Main Campus
Location: Housotn
Name: Rakesh Chary Bangaroj
Type: User
Company: University of Houston - Main Campus
Location: Housotn
All leetcode questions with solutions
Mileago-meter is a simple prototype whose application is to calculate the amount of present in the fuel tank of a vehicle like car, bike etc which makes use of Arduino processor. It is also modeled such that it can predict the further distance a vehicle can travel more with the left-over fuel in it.
React Native (expo) + React Navigation + Hooks + Apollo GraphQL + TypeScript
Efficient and accurate object detection has been an important topic in the advancement of computer vision systems. With the advent of deep learning techniques, the accuracy for object detection has increased drastically. The project aims to incorporate state-of-the-art technique for object detection with the goal of achieving high accuracy with a real-time performance. A major challenge in many of the object detection systems is the dependency on other computer vision techniques for helping the deep learning-based approach, which leads to slow and non-optimal performance. In this project, we use a completely deep learning-based approach to solve the problem of object detection in an end-to-end fashion. The network is trained on the most challenging publicly available dataset (CALTECH 101), on which an object detection challenge is conducted annually. The resulting system is fast and accurate, thus aiding those applications which require object detection.
react first
In this project we are detecting depression from users post, user can upload post in the form of text file, image file or audio file, this project can help peoples who are in depression by sending motivated messages to them. Now-a-days people are using online post services to interact with each other compare to human to human interaction. So by analyzing users post this application can detect depression and send motivation messages to them. Administrator of this application will send motivation messages, links to movies, suggestion of books to boost the mental health, and songs for refreshment to all peoples who are in depression. To detect depression we are using SVM (support vector machine) algorithm which analyses users post and give result as negative or positive. If users express depression words in post then SVM detect it as a negative post else positive post. To implement this project we are using python Speech Recognition API which will read text from audio files and then SVM will analyze that text to detect depression, user can also upload images via post and python Tesseract OCR (Optical Character Recognition) API can read text from uploaded image and then SVM will detect depression from that text, User can upload post in text file also.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.