Pinned Repositories
Facial-Image-Compression
Compression of a 400-images database using PCA
Breast-Cancer-detection-Using-K-NN-clustering
A simple K-NN clustering algorithm to detect whether a cancer is malignant or benign. The data set used is the Wisconsin Breast Cancer dataset.
deep-learning
Deep Learning demos and experiments.
Leave-Approval
MetaData-A-Tool-to-Supplement-Data-Science-Education-For-the-First-Year-Undergraduates
Implementation of the software application developed as a part of our research paper published at ICIET 2020 in Okayama, Japan
MLwR
Machine Learning with R
Neural-networks-implementation
Python implementation of a multi layer perceptron.
Predicting-hotel-ratings-on-zomato
A model to predict hotel ratings available on zomato
Spam-detection
Spam detection and filtering using a Naive Bayes probabilistic classifier
VAE-GAN
A Keras implementation of the VAE-GAN formulated in the paper: Autoencoding beyond pixels using a learned similarity metric.
rahul1801's Repositories
rahul1801/MetaData-A-Tool-to-Supplement-Data-Science-Education-For-the-First-Year-Undergraduates
Implementation of the software application developed as a part of our research paper published at ICIET 2020 in Okayama, Japan
rahul1801/VAE-GAN
A Keras implementation of the VAE-GAN formulated in the paper: Autoencoding beyond pixels using a learned similarity metric.
rahul1801/Breast-Cancer-detection-Using-K-NN-clustering
A simple K-NN clustering algorithm to detect whether a cancer is malignant or benign. The data set used is the Wisconsin Breast Cancer dataset.
rahul1801/deep-learning
Deep Learning demos and experiments.
rahul1801/Leave-Approval
rahul1801/MLwR
Machine Learning with R
rahul1801/Neural-networks-implementation
Python implementation of a multi layer perceptron.
rahul1801/Predicting-hotel-ratings-on-zomato
A model to predict hotel ratings available on zomato
rahul1801/Spam-detection
Spam detection and filtering using a Naive Bayes probabilistic classifier
rahul1801/vaegan-celebs-keras
Autoencoding beyond pixels using a learned similarity metric by Larsen et al. (https://arxiv.org/abs/1512.09300)