Hi. I'm Tega, and this repository is a collation of the projects I'm proud of working on since I started my journey in the data field. I'm a student of Data Science at Axia Africa (Cohort 8).
The main themes of these projects are: exploratory data analysis, which involves data preparation and understanding, machine learning, and web scraping. This is not a finished repository. It would continue to be updated as I explore and advance in the Data Science field.
Cheers to continual learning!
- Python and its libraries
- Scikit Learn
- Pandas
- Numpy
- Matplotlib
- Jupyter Notebook
- Google Colab
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Trained four regression models to predict how much calories an individual burns off during exercise. Afterwhich i evaluated the models and chose the best model for this regression task. Then, i deployed the chosen model on Streamlit so it can accept user input and predict exercise.
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Trained four classification models to predict customer churn behaviour based on . After training, I evaluated the models using performance metrics and selected the most suitable one for the task.
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Used regression techniques to predict house prices based on location, size and its amenities. In this project, I included data preprocessing and feature engineering, visualisation to understand the data and model tuning.
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Scraped data from the WHO website and converted it into a structured Dataframe using Pandas. Then, I exported the data into Excel, CSV, and TSV file formats. This was a really fun task to do.
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I scraped the IMDB website to get its top 25 movies, obtaining information such as the movie titles, genre(s), actors, etc and stored them in a DataFrame. After which, I exported the data in the CSV, TSV, and Excel file formats.
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Scraped a website containing a list of countries and their details, transformed the data into a DataFrame and exported it to CSV, TSV, and Excel file formats.