Machine learning algorithms in Python for real world life science problems.
Projects: Autism Screening, DNA Classification, Breast Cancer Detection, Heart Disease Prediction
Uses SVM, KNN, Neural Networks. Pandas, numpy, sklearn, keras.
The purpose of this project was to understand algorithms available to accomplish a classification task using the Titanic dataset. The data being analyzed deals with different classifications of people, such as gender, age, passenger class, etc. The model is then applied to predict who survived or not.
Project tools: R and Excel used | SVM, naive Bayes, kNN and Random Forest models used
This reports purpose is to use available algorithms to accomplish a classification task. The data is in the form of a csv file and contains attributes on people’s demographics and banking information on if they participate in a Personal Equity Plan (PEP) .
Project tools: R and Excel used| Apriori Algorithm
This assignment explored what information could be gathered about students location, using their zip codes and pining them to a map.This reports purpose is to use available algorithms to accomplish a classification task. The data is in the form of a csv file and contains attributes on people’s demographics and banking information on if they participate in a Personal Equity Plan (PEP) .
Project tools: R and Excel for creation of the maps,charts and graphs| Zipcode, ggmap packages in R
This project involves classifying user rating data based on movie information, specifically the movie genre in this case.
Project tools: R and Excel used
This project explored transformations.
Project tools: R and Excel | plyr, ggplot2 and stringr in R
Final Project that mapped out earthquakes that occurred over the last 50 years.
Project tools: R and Excel for creation of the maps,charts and graphs| Adobe Illustrator for cleaning up of images
Just a simple speed test that shows off the advantages of using the GPU.
Project tools:Uses Python, numpy