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Exam solution for Advanced Data Science course at TU-Berlin
Python 1.25%
Jupyter Notebook 98.75%
songs_data_exam's Introduction
- This is a machine learning model to classify the genre of different songs.
- Dataset Size: 32833 instances, 19 attributes
- Attributes: song metrics, artist names, playlist names
- Machine Learning Type: Supervised Learning, Classification
- Build a Machine Learning Model to predict the genre of a song.
- Jupyter Notebooks with Python 3.7 +
- Library needed pandas ,numpy, seaborn, matplotlib, sklearn.preprocessing,. sklearn.model_selection, sklearn.linear_model, sklearn.metrics, sklearn.tree, sklearn.ensemble, xgboost, sklearn.metrics, warnings.
- Exploratory Data Analysis (EDA)
- Data Preprocessing / Cleaning
- Building Machine Learning Model
- Evaluating and Explaining Model Performance
- Conclusions, Limitations and Next Steps
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