I worked several years as a conservation ecology researcher at Phillips-University Marburg, where I fell in love with analyzing data in R and extracting meaningful insights. This love for data (and the dislike for writing publications) made me realize that I would rather be a Data Scientist. To kickstart my career transition I joined a Data Practitioner bootcamp at neuefische, where I learned to use pandas and numpy in python, gather data with SQL and FastAPI, train and track machine learning models in scikit-learn and MLFlow, deploy them as apps with streamlit and showcase analytical findings in Tableau. Ultimately, I and three other trainees used our new skills in a capstone project where we became the Paw Predictors and we build a ML model to predict the adoption speed of shelter animals. More infos can be found in the linked repo below.
Pinned Loading
-
LanaCasselmann/ds_capstone_pet_adoptability
LanaCasselmann/ds_capstone_pet_adoptability Public -
Levaldo42/ds-ml-financial-inclusion-project
Levaldo42/ds-ml-financial-inclusion-project PublicThe financial inclusion is considered as one of the main topics for poverty reduction in the world.
Jupyter Notebook 1
Something went wrong, please refresh the page to try again.
If the problem persists, check the GitHub status page or contact support.
If the problem persists, check the GitHub status page or contact support.