Kunwar Vikrant (@kunwar-vikrant)
  • Stars
    star
    130
  • Global Rank 171,488 (Top 6 %)
  • Followers 13
  • Following 9
  • Registered over 6 years ago
  • Most used languages
    C++
    9.4 %
    JavaScript
    6.3 %

Top repositories

1

Microsoft-Malware-Detection

This repo demonstrates a real world case study and aims to solve a business problem, that is to predict the probability of each data-point belonging to each of the nine classes of malware.
Jupyter Notebook
8
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2

New-York-City-Taxi-Demand-Prediction

This repo demonstrates a real world case study and aims to solve a business problem, i.e to find number of pickups, given location cordinates(latitude and longitude) and time, in the query reigion and surrounding regions
Jupyter Notebook
5
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3

Human-Activity-Recognition

This repo demonstrates a real world case study and aims to solve a business problem i.e, to build a model that predicts the human activities such as Walking, Walking_Upstairs, Walking_Downstairs, Sitting, Standing or Laying.
Jupyter Notebook
4
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4

Self-Driving-Car

This repo demonstrates a real world case study.The aim of this project is to create a model which can be used to design an autonomous vehicle system.
Jupyter Notebook
4
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5

K-means-Agglomerative-DBSCAN-clustering-algorithms-on-Amazon-reviews-data-set

This is a notebook which demonstrates results of applying K-means, Agglomerative, DBSCAN clustering algorithms on Amazon reviews data set Algorithm on the dataset which consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review.
Jupyter Notebook
4
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6

Personalized-Cancer-Diagnosis

This repo demonstrates a real world case study and aims to solve a business problem, that is to classify the given genetic variations/mutations based on evidence from text-based clinical literature.
Jupyter Notebook
3
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7

Facebook-Friend-Recommendation-Engine

This repo demonstrates a real world case study and aims to solve a business problem i.e, have to predict missing links to recommend users (Link Prediction in graph).
Jupyter Notebook
3
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8

Quora-Question-Pair-Similarity

This repo demonstrates a real world case study and aims to solve a business problem, that is to Identify which questions asked on Quora are duplicates of questions that have already been asked.
Jupyter Notebook
3
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9

Decision-Trees-on-Amazon-Reviews-dataset

This is a notebook which demonstrates results of applying Decision Trees Algorithm on the dataset which consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review.
Jupyter Notebook
3
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10

Netflix-Movie-Recommendation-Engine

This repo demonstrates a real world case study and aims to solve a business problem, that is to Predict the rating that a user would give to a movie that he has not yet rated and minimize the difference between predicted and actual rating (RMSE and MAPE) .
Jupyter Notebook
3
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11

Codechef

Some rated codechef problems
C++
2
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12

Try-various-CNN-networks-on-MNIST-dataset

This repo demonstrates the result of applying various CNN networks on the MNIST dataset.
Jupyter Notebook
2
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13

LeetCode-Problems

C++
2
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14

Hackerrank-

This repo contains some Graphs and DP questions of hackerrank platform.
C++
2
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15

Continuous-Control

Using reinforcement learning techniques to train an agent to maintain its position at the target location for as many time steps as possible.
Jupyter Notebook
2
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16

Cloud-ML-Demo

JavaScript
2
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17

Navigation-RL

Using reinforcement learning techniques to train an agent to navigate (and collect bananas!) in a large, square world.
Jupyter Notebook
2
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18

Stack-Overflow-Tag-Prediction

This repo demonstrates a real world case study and aims to solve a business problem, i.e to predict as many tags as possible with high precision and recall.
Jupyter Notebook
2
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19

Let-s-Learn-Tennis

Using reinforcement learning techniques to train two agents to play a game of tennis and keep the ball in play
Jupyter Notebook
2
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20

Haberman-Dataset-EDA

This is an Exploratory Data Analysis on the dataset which contains cases from a study that was conducted between 1958 and 1970 at the University of Chicago's Billings Hospital on the survival of patients who had undergone surgery for breast cancer.
Jupyter Notebook
2
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21

LSTM-on-Amazon-Reviews-DataSet

This is a notebook which demonstrates results of applying LSTM on the amazon reviews dataset. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review.
Jupyter Notebook
2
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22

Amazon-Apparel-Recommendation

This repo demonstrates a real world case study and aims to solve a business problem, that is to suggest similar apparels based on user's interest.
Jupyter Notebook
2
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23

Random-Forest-and-GBDT-on-Amazon-Reviews

This is a notebook which demonstrates results of applying Random Forest and GBDT Algorithm on the dataset which consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review.
Jupyter Notebook
2
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24

Support-Vector-Machines-SVMs-

This is a notebook which demonstrates results of applying SVM Algorithm on theAmazon fine food review Dataset. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review.
Jupyter Notebook
2
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25

Stochastic-Gradient-Descent-for-Linear-Regression-

This is a notebook which demonstrates results of applying Stochastic Gradient Descent for Linear Regression algorithm on the dataset which consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review.
Jupyter Notebook
2
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26

Truncated-SVD-algorithm-on-Amazon-reviews-dataset

This is a notebook which demonstrates results of Truncated SVD algorithm on Amazon reviews data set which consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review.
Jupyter Notebook
2
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27

Naive-Bayes-on-Amazon-Reviews

This is a notebook which demonstrates results of applying Naive Bayes Algorithm on the dataset which consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.
Jupyter Notebook
2
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28

TSNE-Visualization

This is a notebook to demonstrate TSNE visualization of the dataset which consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.
Jupyter Notebook
2
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29

Logistic-Regression

This is a notebook which demonstrates results of applying Logistic Regression Algorithm on the dataset which consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.
Jupyter Notebook
2
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30

k-NN-on-Amazon-Reviews

This is a notebook which demonstrates results of applying k-nearest neighbours on the dataset which consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.
Jupyter Notebook
2
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31

TensorFlow-and-Keras-Build-various-MLP-architectures-for-MNIST-dataset

This repo demonstrates the result of applying various MLP architectures on the MNIST dataset.
Jupyter Notebook
2
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32

kunwar-vikrant.github.io

JavaScript
1
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