Project Description

During the lecture “Machine Learning”, I did the three required projects. To be able to write the exam, one had to pass the public baseline for each project. Each project had to be written in a given framework in Python.

Project 1: Predict a person’s age from a brain scan. (more information: ml-project-1)
For this project, the training data consisted of 278 different brain scans and was about 8GB. The test data contained 138 brain scans.
My rank: 52/461 => top 12%

Project 2: Predict a person’s disease stage from their brain scan. (more information: ml-project-2)
For this project, the training data consisted of 278 different brain scans and was about 8GB. The test data contained 138 brain scans.
My rank: 45/381 => top 12%

Project 3: Echocardiogram classification. (more information: ml-project-3)
For this project, the training data consisted of 6821 different time-series data about the heart-frequency and was about 1GB. The test data contained 1706 records.
My rank: 23/383 => top 7%

My tasks

  • Work with big datasets
    • Project 1: 8 GB (278 training samples; 138 test samples; 6’443’008 features)
    • Project 2: 8 GB (278 training samples; 138 test samples; 6’443’008 features)
    • Project 3: 1.16 GB (6822 training samples; 1706 test samples; 18’286 features)
  • Analysis of existing papers to find usable features.
  • Implementing the machine learning pipeline in Python with Numpy, SkLearn, and BioSPPy.