Nikhil Kumar (@nikhilkr29)
  • Stars
    star
    31
  • Global Rank 479,903 (Top 17 %)
  • Followers 4
  • Following 1
  • Registered almost 5 years ago
  • Most used languages
    MATLAB
    14.3 %
    HTML
    14.3 %
    C++
    14.3 %
  • Location 🇮🇳 India
  • Country Total Rank 23,307
  • Country Ranking
    MATLAB
    503
    C++
    8,641

Top repositories

1

Email-Spam-Classifier-using-Naive-Bayes

A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of email subject is first used to train the classifier and then a previously unseen email subject is fed to predict whether it is Spam or Ham.
Jupyter Notebook
9
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2

AIR_QUALITY_INDEX_PREDICTION

Predicts the Quality of Air based on various factors .Different Supervised Machine Learning Algorithms were used like Linear Regression, KNN, Decision Tree, XgBoost. The best accuracy was obtained using Xgboost.
Jupyter Notebook
6
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3

Pan-Tomkins-Method-for-QRS-Detection

Implementing the Pan–Tompkins method for QRS detection using a simple threshold-based method to detect QRS complexes and then finding out the QRS Width and Heart Rate for the given data.
MATLAB
5
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4

Access-Control-using-Machine-Learning

We aim to build up an employee access control system, which automatically approves or reject employee’s resource application.
Jupyter Notebook
3
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5

My-Spoj-Solutions

My solutions in C++ to some problems hosted on Spoj
C++
2
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6

nikhilkr29

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7

Car-Price-Prediction

A car price prediction model that predicts the price of a car based on various data like fuel type, distance driven, year of purchase ,etc. given as a input by the user. The dataset was found on Kaggle and the machine learning model used for making the price prediction was Random Forest Regressor
Jupyter Notebook
2
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8

Shakti-Excellence-is-not-gender-specific

A MIS software for IMO under Rashtriya Mahila Kosh with individual password protected login portals and databases for different IMOs for maintenance of records of loan given .Also includes a help and complaint feature which directly sends complaints to RMK and also includes a loan calculator
HTML
2
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