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bank_costumer_prediction icon bank_costumer_prediction

This is an artificial neural network that is trained with 10'000 people details who were or are the costumers of the respective bank. This ANN is going to take the required details of a costumer and predict if e is going to leave the bank or not. This model is totally made using the Keras library by running tensorflow backend and Numpy for numerical computations.

dcgan-tensorflow icon dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

housing-sale-price-prediction icon housing-sale-price-prediction

"Buying a house is a stressful thing." We built a model to predict the prices of residential homes in Ames, Iowa, using advanced regression techniques. This model will provide buyers with a rough estimate of what the houses are actually worth. We first analyzed the data to find trends. Then dimensionality reduction was performed on the dataset using PCA algorithm and feature selection module in sklearn package for python 3.5. The final house prices are predicted using linear regression models like Ridge and Lasso. We also utilised advanced regression techniques like gradient boosting using XGBoost library in python 3.5.

occluded-offline-hccr icon occluded-offline-hccr

Occluded Offline Handwritten Chinese Character Recognition Using Deep Convolutional Generative Adversarial Network and Improved GoogLeNet

predicting-total-charges-of-hospital icon predicting-total-charges-of-hospital

Naive Bayes to predict total charges of hospital using parameters like length of stay, diagnosis code, diagnosis indicator and so on. Web application using flask and python which allows user to select attributes otherwise it will consider all attributes by default and gives back predicted cost.

python- icon python-

Practice of book whose name is python deep learning

reconnet icon reconnet

REcurrent COnvolution Neural NETwork for occluded object recognition

sentiment_analysis icon sentiment_analysis

I have built a model which will predict the sentiment of movie reviews. I used Naive-Bayes, SVM, and RNN+LSTM based model to obtain really good result.

sgen-pytorch icon sgen-pytorch

PyTorch implementation of "Sequential Gating Ensemble Network for Noise Robust Multi-Scale Face Restoration"

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