Exploratory Data Analysis with TSNE ON_ DonorsChoose data set

Unsupervised-ML-t-SNE-Data-Mining-Cancer. Import Libraries, Import Dataset, Convert data to array format, Separate array into input and output components, TSNE implementation, Cluster Visualization

Creating empty dataframe, data normalization, Dimensionality reduction, Outlier detection, Overfitting of model and its solution, Remove column with zero values, Replace NA with zeros.

MNIST Digit recognition using machine learning techniques

Analysing different dimensionality reduction techniques and svm

This project used NLP to topic model classical music based on musical chords. Classical composers were then clustered using the topics from the NLP, and then a neural network was used to generate original music based on trained music of the different classical composers. All of these metrics were used as a model for complexity of music.

Word Embedding visualization with T-SNE (t-distributed stochastic neighbor embedding) for BERT, ALBERT, ELMO, ELECTRA, XLNET, GLOVE.

3D T-SNE graphs with sliders and checkboxes to visualize the T-SNE cloud at every epoch for specific labels. Optionally you can also track specific datapoint by labeling it with a unique marker.

Data visualization by implementing T-sne and PCA

Testing AutoNovel and UNO novel-class-discovery techniques to assess their prerformances under different settings. Plot of tSNE to evaluate clustering capabilities for known and new classes

Understand and Run Naive Bayes Algorithm on Dry Beans dataset

A python based tool for clustering text , CSV and logs.

Predicting Colorado forest cover types using diverse ML models for classification. Baseline creation, feature selection, comparison, and tuning optimize accuracy in this University of Ottawa Master's Machine Learning course final project (2023).

I am on the Advisory Services Team of a financial consultancy. One of MY clients, a prominent investment bank, is interested in offering a new cryptocurrency investment portfolio for its customers. The company, however, is lost in the vast universe of cryptocurrencies. They’ve asked me to create a report that includes what cryptocurrencies are o…

For the Unsupervised Machine Learning [PPGEEC2325] course by Professor Luiz Affonso at UFRN, this application displays word2vec embeddings using PCA and t-SNE, allowing users to easily grasp linguistic patterns.