Anish Kumar Saha's repositories
Shape-Shifter-Android-Game
This repository contains all the scripts needed in the development of the above-mentioned application. The game was coded in C# in the Unity Platform. The link for download is ----> https://play.google.com/store/apps/details?id=com.Pixellent.ShapeShifter
Sempal-backend
Backend implementation for the capstone SEMPAL (Server Monitored Prioritized Automated Load-Shedding)
Blockchain-Exam-Portal
This repo contains all the source code files necessary to build a simple test portal for students on the Ethereum network. Upon scoring beyond a pre-set score, the students are gifted with a suitable amount of ether. Note: Some changes are required to make the ether transaction between two accounts bug-free. Don't forget to configure the truffle-config.js file in your project directory.
Decentralized-Voting-app-Demo-
A decentralized voting app hosted on the local Ethereum network. Five candidates participate in a model election and ten model voting accounts.
devfestweb
web components for DevFest'18
Google-Map-API-app
It's a small app created for survivors to communicate with each other, help each other during a zombie apocalypse. A simulation app basically with fully function google map.
Hackerrank-solutions
Solution to some of the practice problems from the Hackerrank site, covering some important topics. Any changes to the solution or more optimized coding suggestions will be highly appreciated. Feel free to dig in.
Hackerrank-solutions-2
Second set of Hackerrank code solutions.
HackerrankSolns3
Third set of solutions to different problems in Hackerrank site.
Interviewbit-Solutions
This contains the code solutions to the miscellaneous questions asked in the contests hosted on InterviewBit. Any changes or suggestions for more optimal code would be highly appreciated. More to come.
k8s-web-app-kaiyo
A web app to deploy using the kuberneters. The application contains the backend in node js and frontend in react and redux. Mostly boilerplate app.
machine-coding-interview-101
A collection of some of the questions asked in the machine coding round of a technical interview.
Movie-Rating-Prediction
A regression system was designed that predicts the IMDb rating of a movie. A movie viewer would otherwise have to rely on a critic's review or self-instincts. A dataset, obtained from Kaggle, contains certain attributes (such as genre, duration, names of actor, director, number of voters for the rating, plot and keywords, language, etc.) and performance rating of over 5000 movies. On observation, the dataset is preprocessed in order to fill missing data and convert categorical features to numerical. Several hypotheses are selected and a few not chosen due to unfavorable conditions observed. A 5-fold cross-validation on the hypotheses set exhaustively searches for the most optimum hyperparameters of the model with the least MSE and helps curtail overfitting. Random forest regressor is chosen due to its low MSE and simplicity. The model is retrained and gives a better coefficient of determination on the test set when compared to previous techniques on Kaggle. Software: Python with use of Scikit-learn library
Nim-MiniMax
Ultron v/s a human (you) take on a subtraction game battle !
python-pip-package
Python Pip Package Test
SupakiAssignment
SupaKI
TARP-Accident-Detection
Technical Answers to Real world Problems