Recommendation Systems
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Updated
May 24, 2023 - Jupyter Notebook
Recommendation Systems
Data Science Assignment
Performance of Kmean clustering algorithm on Myopia dataset
MNIST dataset
T-Distributed Stochastic Neighbor Embedding Library
A simple Jupyter notebook to visualize data in latent space using dimensionality reduction techniques.
Comparison of the Stochastic Neighbor Embedding(SNE) and the t-distributed SNE algorithms
EComp: Evolutionary Compression of Neural Networks Using a Novel Similarity Objective
Interactive tool for building correlation maps between governments worldwide.
It has the comparison study on dimension reduction techniques PCA and t-SNE on MNIST Digit Recognitaion Dataset
Use unsupervised learning to cluster the Cryptocurrency using dimensionality reduction with PCA & t-SNE and K-Means.
HDP + T-SNE + k-NN applied to topic modeling
Dimensionality reduction and visualization techniques t-stochastic neighbour embedding (t-SNE) and uniform manifold approximation and projection (UMAP) were used to evaluate National Renewable Energy Laboratory’s (NREL) market segmentation for rooftop solar technical potential based on small, medium, and large classification labels. The medium a…
Deep-based generation of Wing Interferential Patterns Images for the surveillance of blood-sucking insect population by Machine learning algorithms(Generative adversarial networks, Adversarial Autoencoders). Summer intership, research project
R package for automatic hyper parameter tuning and ensembles with deep learning, gradient boosting machines, and random forests. Powered by h2o.
Analysing different dimensionality reduction techniques and svm
Applying NLP to understand people's sentiment about Covid-19 and Government actions in Italy, conditional on their political affiliation.
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