AI and Machine Learning
The following Jupyter Notebooks were completed as part of a post graduate program in AI/ML at the University of Texas at Austin.
Data Science Concepts
Fundamentals of Artificial Intelligence and Machine Learning: intro to Data Science
Supervised Learning
Predicting probability of current bank customers accepting a newly offered loan product
Ensemble Techniques
Determining efficacy of alternate methods for diagnosing Parkinson’s Disease
Feature Selection and Model Tuning
Creating an alternate, sustainable recipe for construction concrete
Unsupervised Learning
Using k-means and hierarchical clustering to segment banking customers
Neural Networks
Using Tensorflow and Keras to identify house numbers on “street view” images
Computer Vision
Attempting to build a model that can diagnose COVID-19 with an x-ray image
Natural Language Processing
Pre-processing text and building a model to classify products based on descriptions