UNSUPERVISED LEARNING PROJECT ON HEALTH DATA
Budget: $10 – $30 USD
I am looking for a data scientist who can help me with an unsupervised learning project on health data.
Algorithm:
- I would like to use various algorithms to analyze the data.
Data:
- The project will involve analyzing the frequency of mental health disorders among tech workers.
Focus:
- Since the data has high dimensionality and complexity , we should provide a better overview over the data in ways which are more easily interpretable and transferable to improvements.
The goal is to categorize participants of the survey according to their answers and to provide visualizations supporting the interpretation of these clusters. These visualizations should convey a perspective onto the data set, which is reduced in complexity and dimensionality and yet preserving the main characteristics of the whole available data.
You should also provide insight into each individual identified cluster of participants and their main characteristics.
Skills and Experience:
- Strong knowledge and experience in unsupervised learning algorithms.
- Proficiency in data analysis and interpretation, specifically with clinical test results.
- Understanding of health data and disease patterns.
- Ability to extract meaningful insights and patterns from the data.
Algorithm:
- I would like to use various algorithms to analyze the data.
Data:
- The project will involve analyzing the frequency of mental health disorders among tech workers.
Focus:
- Since the data has high dimensionality and complexity , we should provide a better overview over the data in ways which are more easily interpretable and transferable to improvements.
The goal is to categorize participants of the survey according to their answers and to provide visualizations supporting the interpretation of these clusters. These visualizations should convey a perspective onto the data set, which is reduced in complexity and dimensionality and yet preserving the main characteristics of the whole available data.
You should also provide insight into each individual identified cluster of participants and their main characteristics.
Skills and Experience:
- Strong knowledge and experience in unsupervised learning algorithms.
- Proficiency in data analysis and interpretation, specifically with clinical test results.
- Understanding of health data and disease patterns.
- Ability to extract meaningful insights and patterns from the data.