Teaching Assistant Evaluation
University of Wisconsin-Madison is concerned about the performance of its teaching assistants. They’ve been keeping a proper record of various performance parameters and have even manually assigned them scores.
Your task is to determine the
Performance of a teaching assistant i.e to find which of the following categories (1=Low, 2=Medium, 3=High) the TA belongs to.
Submissions are evaluated using Accuracy Score. How do we do it?
Once you generate and submit the target variable predictions on evaluation dataset, your submissions will be compared with the true values of the target variable.
The True or Actual values of the target variable are hidden on the DPhi Practice platform so that we can evaluate your model's performance on unseen data. Finally, an Accuracy score for your model will be generated and displayed
About the dataset
The data consist of evaluations of teaching performance over three regular semesters and two summer semesters of 151 teaching assistant (TA) assignments at the Statistics Department of the University of Wisconsin-Madison. The scores were divided into 3 roughly equal-sized categories ("low", "medium", and "high") to form the class variable.
To load the dataset in your jupyter notebook, use the below command:
import pandas as pd ta_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/Teaching_Assistant_Evaluation/Training_set_ta.csv')
- ES: Whether the TA is an English Speaker or not - binary (1 = English Speaker, 0 = Non - English Speaker)
- Instructor: Course instructor - categorical (25 categories)
- Course: Course - categorical (26 categories)
- Semester: Summer or Regular - binary (1=Summer, 2=Regular)
- Class_Size: Size of the class - numerical
- Performance: Teaching performance over three regular semesters and two summer semesters - categorical (1=Low, 2=Medium, 3=High)
Load the evaluation data (name it as 'evaluation_data'). You can load the data using the below command.
evaluation_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/Teaching_Assistant_Evaluation/Testing_s
This dataset was downloaded from the UCI Machine Learning Repository - https://archive.ics.uci.edu/ml/datasets/Teaching+Assistant+Evaluation
To participate in this challenge either you have to create a team of atleast members or join some team