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A. UBDA Computing Intensive Service

Data Transfer from a User System to UBDA Platform

 UBDA - Data Transfer

Python examples for ML/DL





Examples Details

Deep Learning

Deep learning using cotton images

Deep learning, tensorflow, sequential, CNN, binary labels


Deep learning using ball images

Deep learning, tensorflow,sequential, CNN, multi-labels


Deep learning using chest xray images

TensorFlow, binary labels, prediction (neural network)


Deep learning using traffic sign images

TensorFlow, multi-labels, prediction (neural network)



Classification analysis of student information

Linear Regression, Decision Trees, Logistic Regression, Random Forest

Neural Networks, Support Vector Machines


Classification analysis for flower images

Logistic Regression, Linear Discriminant Analysis, K-Nearest Neighbors, Decision Trees,

Random Forests, Gaussian Naive Bayes and Support Vector Machine



Clustering analysis using K-means



Text Analysis

Text analysis using nltk for sentiment prediction

CountVectorizer, Tfidf, Sentiment Prediction (naive_bayes)


Convex Optimization

Convex optimization using CVXPPY for portfolio optimization

Portfolio optimization, Linear Programming


Convex optimization using CVXOPT for floor planning

Floor planning, Linear Programming


Demo Video

Basic operation in ubdaplatform (Student / Staff)

B. UBDA Big Data Service

a. Virtual Machine

b. Online JupyterLab Development Tool with GPU User Guide

Demo Video

Basic operation in ubdalab (Student / Staff)