AHEAD_Task

The task from AHEAD tech

Task1 (Watch detail from -> AHEAD.py & AHEAD.ipynb) :

• AHEAD.py

• AHEAD.ipynb

• TASK: There are a group of patients who were diagnosed either COVID-19 positive (sick) or negative (healthy). Each FCS file represents the specimen collected from one patient. Build an automatic predictor using a ML model of your selection, the labels provided in the “EU_label.xlsx” as ground truth, and marker-channels with “use” = 1 in “”EU_marker_channel_mapping.xlsx” as ” as data features

Step :

• 1.Concat FCSdata with FeatureName
• 2.Data Analyze
• 3.Concat dataframe with label
• 4.Label Encoding
• 5.Training model by using all the patients data
• 6.evaluate the performance of the model

Bonus Question : (Watch detail from -> Bonus Question.ipynb)

• Bonus Question.ipynb

• Below are plots of selected cell surface biomarkers of blood cell samples. Researchers are interested in picking out cells marked in yellow (accupying a high-density chunk at the bottom-right) for further analysis. How would you suggest a method to automatically identify these cells?