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1. Titanic-Survivor-Prediction Titanic-Survivor-Prediction Public

   Forked from mrc03/Titanic-Survivor-Prediction

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2. IBM-HR-Analytics-Employee-Attrition-Performance IBM-HR-Analytics-Employee-Attrition-Performance Public

   Forked from mrc03/IBM-HR-Analytics-Employee-Attrition-Performance

   The IBM HR Analytics Employee Attrition & Performance dataset from the Kaggle. I have first performed Exploratory Data Analysis on the data using various libraries like pandas,seaborn,matplotlib et…

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3. Cats-vs-Dogs-CNN-Keras Cats-vs-Dogs-CNN-Keras Public

   Forked from mrc03/Cats-vs-Dogs-CNN-Keras

   The famous Cats-vs-Dogs dataset. I have used a self laid ConvNet to classify the image into 2 classes either a Dog or a Cat. The images used are of 100*100 pixels each. The images are first convert…

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4. Flower-Recognition-Kaggle-CNN-Keras Flower-Recognition-Kaggle-CNN-Keras Public

   Forked from mrc03/Flower-Recognition-Kaggle-CNN-Keras

   The dataset is Flower Recognition on Kaggle. The dataset consists of 4232 images each of different pixel values. Each of the image can be classified into either of 5 types-> 'Daisy','Rose' etc... .…

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5. Collaborative-Filtering-using-Matrix-Factorization-Neural-Network Collaborative-Filtering-using-Matrix-Factorization-Neural-Network Public

   The Movielens 100K dataset. The dataset contains of around 1lac ratings given to about 9066 movies by around 671 users. I have implemented Collaborative Filtering using Matrix Factorization with Ke…

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6. Movie-RecSys-using-Surprise-Library Movie-RecSys-using-Surprise-Library Public

   The dataset used is the Movielens100K dataset. I have then splitted the dataset into training and validation sets. Then I have studied the test and the train sets and also created the utility matri…

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