kunwar-vikrant/Haberman-Dataset-EDA

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kunwar-vikrant/Haberman-Dataset-EDA

kunwar-vikrant

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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.

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

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

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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.

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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.

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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.

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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.

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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).

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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.

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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.

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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) .

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Codechef

Some rated codechef problems

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

This repo demonstrates the result of applying various CNN networks on the MNIST dataset.

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LeetCode-Problems

Hackerrank-

This repo contains some Graphs and DP questions of hackerrank platform.

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.

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Cloud-ML-Demo

Navigation-RL

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

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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.

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Let-s-Learn-Tennis

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

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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.

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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.

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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.

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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

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.

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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

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.

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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

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

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

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

kunwar-vikrant.github.io