On the Amazon fine food review, TSNE is applied

Recommendation Systems

Performance of Kmean clustering algorithm on Myopia dataset

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.

MNIST dataset

T-Distributed Stochastic Neighbor Embedding Library

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

Applying NLP to understand people's sentiment about Covid-19 and Government actions in Italy, conditional on their political affiliation.

Machine-Learning-Algorithms-From-Scratch

Visualizing word similarities in Adventures of Huckleberry Finn using TSNE

Working on Cifar-10 Dataset and Finding out its best SVM Model.

Data visualization by implementing T-sne and PCA

My Dissertation evaluates methods against S&P 500 US stock data from Yahoo Finance, aiming to offer a concise financial market snapshot

Clustering sentences/text snippets by employing Sentence Embeddings (e.g., BERT, Universal Sentence Encoder etc) & various clustering algorithms like T-SNE, K-Means etc.