DataScience-Statistics,Machine Learning,AppliedAI
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Updated
Feb 16, 2018 - Jupyter Notebook
DataScience-Statistics,Machine Learning,AppliedAI
Application of Malay Word2Vec and its visualization in 2D and 3D space.
A multi-class classification problem where the task is to classify a file to one of 9 types of Malware usually found in a Windows system, using information from the raw data and metadata of the file.
Automatic classification of consumer goods from text and images
Used several clustering algorithms to explore whether the patients can be placed into distinct groups so that myopia, or nearsightedness can be predicted.
t-distributed stochastic neighborhood embedding (t-SNE) is a unsupervised non-linear dimensionality reduction and data visualization technique. The math behind t-SNE is quite complex but the idea is simple. It embeds the points from a higher dimension to a lower dimension trying to preserve the neighborhood of that point. I compared PCA and t-SN…
Deep Learning vs Tranditional ML methods for TB Drug Resistance prediction from Genomic data
This is the repository for my Project Melvin the Mind. As of 3rd of August 2017 12:20 AM I hereby officially start this project. The aim of this project is to create an open source program/AI whose purpose is to create how to instructions for completing tasks based on data analyzed from its library. All help is greatly welcomed including, but no…
Mapping academic research papers into a graph using machine learning
Dimensionality Reduction and Data Visualization with MNIST Dataset.
learning GNNs
Rapid analysis of scientific papers from bioRxiv and PubMed
Using "t-SNE trajectories" for integrated visualization of multi-dimensional longitudinal trajectory datasets.
Unsupervised classification of products based on their text description (NLP) or image (computer vision)
identify segments of customers by geography using unsupervised learning
Cryptocurrency classification system using dimensionality reduction with PCA & t-SNE and cluster analysis with K-Means
Implementing an MLP to classify the IRIS dataset and analysing using Tensorboard
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