Pinned Repositories
6Apr_Live
Java DS ALGO Live Class Notes
Algorithm-Practice
Practicing algorithms
BLOCKCHAIN-Progressive-Web-Application
Clock-Android-App-in-Java
CodingBlocks-Answers
Hacktoberfest
COVID-19-Detection-by-Symptoms
This project is my contribution to helping to analyze the probability of a person having the infection. Technologies that were made to convert information so that it can be accessible to computers are used to aid people and I can contribute to a social cause. COVID 19 Detector is a Web Application Prototype Developed by ME and built for Doctors to find out whom to test for the infection first under a limited testing capacity by finding out the probability of a person having the infection.
Credit-Card-Fraud-Detection-Using-Machine-Learning
The main concern of this research was to detect least and accurate false fraud detection. Credit card fraud is lack of security. Credit Card Fraud can be used for applications as paying with credit card make it easier to avoid loses from fraud. This project has examined the performance of five kinds of classification models namely Random Forest Algorithm, Decision Tree Algorithm, Naïve Bayes, KNN Algorithm, SVM Algorithm. A real-life dataset on credit card transactions is used in our experiment. Among all the methods, the SVM one has the maximum accuracy. Although SVM obtains good results on small set data, there are still some problems such as imbalanced data. Our future work will focus on solving these problems. For example, the voting mechanism assumes that each of base classifiers has equal weight, but some of them may be more important than others. Therefore, we also try to make some improvement for this algorithm. The results indicate the optimal accuracy for SVM, Naïve Bayes, KNN, Random Forest Classification and Decision Tree Classification are 91.87%, 90.24%, 89.83%, 91.05% and 88.62% respectively.
data-structures-in-real-life
Course Repository for Course - Data Structures in Real Life (Projects)
Hacktoberfest
Make your first PR! ~ A beginner friendly repository made specifically for open source beginners. Add any program under any language (it can be anything from a hello-world program to a complex data structure algorithm to a blog!) or update the existing one. Just make sure you add the program under the correct language directory. Happy coding!
SARS-CoV-2-COVID-19-Prediction-using-Corona-Virus-Genome-Sequence
SARS CoV-2 / COVID-19 Prediction using Corona Virus Genome Sequence. Metagenomic RNA sequencing of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like corona viruses (genus Beta corona virus, sub genus Sarbecovirus) that had previously been found in bats in China.So we have done this and explained some facts with the help of some graphs made through matplot.
AnubhavMishra22's Repositories
AnubhavMishra22/6Apr_Live
Java DS ALGO Live Class Notes
AnubhavMishra22/BLOCKCHAIN-Progressive-Web-Application
AnubhavMishra22/data-structures-in-real-life
Course Repository for Course - Data Structures in Real Life (Projects)
AnubhavMishra22/Hacktoberfest
Make your first PR! ~ A beginner friendly repository made specifically for open source beginners. Add any program under any language (it can be anything from a hello-world program to a complex data structure algorithm to a blog!) or update the existing one. Just make sure you add the program under the correct language directory. Happy coding!
AnubhavMishra22/SARS-CoV-2-COVID-19-Prediction-using-Corona-Virus-Genome-Sequence
SARS CoV-2 / COVID-19 Prediction using Corona Virus Genome Sequence. Metagenomic RNA sequencing of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like corona viruses (genus Beta corona virus, sub genus Sarbecovirus) that had previously been found in bats in China.So we have done this and explained some facts with the help of some graphs made through matplot.
AnubhavMishra22/Algorithm-Practice
Practicing algorithms
AnubhavMishra22/Clock-Android-App-in-Java
AnubhavMishra22/CodingBlocks-Answers
Hacktoberfest
AnubhavMishra22/COVID-19-Detection-by-Symptoms
This project is my contribution to helping to analyze the probability of a person having the infection. Technologies that were made to convert information so that it can be accessible to computers are used to aid people and I can contribute to a social cause. COVID 19 Detector is a Web Application Prototype Developed by ME and built for Doctors to find out whom to test for the infection first under a limited testing capacity by finding out the probability of a person having the infection.
AnubhavMishra22/Credit-Card-Fraud-Detection-Using-Machine-Learning
The main concern of this research was to detect least and accurate false fraud detection. Credit card fraud is lack of security. Credit Card Fraud can be used for applications as paying with credit card make it easier to avoid loses from fraud. This project has examined the performance of five kinds of classification models namely Random Forest Algorithm, Decision Tree Algorithm, Naïve Bayes, KNN Algorithm, SVM Algorithm. A real-life dataset on credit card transactions is used in our experiment. Among all the methods, the SVM one has the maximum accuracy. Although SVM obtains good results on small set data, there are still some problems such as imbalanced data. Our future work will focus on solving these problems. For example, the voting mechanism assumes that each of base classifiers has equal weight, but some of them may be more important than others. Therefore, we also try to make some improvement for this algorithm. The results indicate the optimal accuracy for SVM, Naïve Bayes, KNN, Random Forest Classification and Decision Tree Classification are 91.87%, 90.24%, 89.83%, 91.05% and 88.62% respectively.
AnubhavMishra22/gimmie-sticker
Trade a Pull Request for a Sticker
AnubhavMishra22/Git-Practice
AnubhavMishra22/Google-foo.bar-Challenge-Answers
AnubhavMishra22/graduation
$ git remote <graduation> yearbook
AnubhavMishra22/GUI-Calculator-using-Java-Swings-AWT
AnubhavMishra22/hack-jaipur-2020
Template for HackJaipur 2020 Hackathon on GitHub Actions
AnubhavMishra22/Hospital-Management-System
AnubhavMishra22/java_random
AnubhavMishra22/js-assignments
Javascript assignments, tasks and katas
AnubhavMishra22/Kotlin-Weather-Application
AnubhavMishra22/My-Persistent-Storage-Application
AnubhavMishra22/My-Portfolio-Website
AnubhavMishra22/Profit-Estimation-Of-A-Company-Using-1000_Companies-Dataset
AnubhavMishra22/profit_estimation_of_companies
profit estimation of companies with linear regression
AnubhavMishra22/resilientdb
ResilientDB: Global-Scale Sustainable Blockchain Fabric
AnubhavMishra22/Suduko-Solver-In-Java
AnubhavMishra22/Vehicle_Detection