https://github.com/brendandasilva/applieddatascience
4 projects from Applied Data Science
https://github.com/brendandasilva/applieddatascience
data-science numpy pandas python
Last synced: 4 months ago
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4 projects from Applied Data Science
- Host: GitHub
- URL: https://github.com/brendandasilva/applieddatascience
- Owner: BrendanDasilva
- Created: 2024-11-15T19:11:32.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-10T15:40:33.000Z (12 months ago)
- Last Synced: 2025-08-02T11:49:44.234Z (6 months ago)
- Topics: data-science, numpy, pandas, python
- Language: Jupyter Notebook
- Homepage:
- Size: 1020 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Applied Data Science
This repository contains assignments from my Applied Data Science coursework. Each assignment explores different aspects of data analysis, machine learning, and visualization using Python.
## Assignments
### 1. Working with NumPy and Matplotlib
This assignment covers fundamental operations in NumPy for numerical computing and visualization using Matplotlib.
📺 **Video Walkthrough:** [YouTube Link](https://youtu.be/OxPikMOtPuY)
### 2. Using a Decision Tree Model in SKLearn
Implementation of a decision tree classifier using the `sklearn` library, covering data preprocessing, model training, and evaluation.
📺 **Video Walkthrough:** [YouTube Link](https://youtu.be/0dGOBe4qfzQ)
### 3. House Prices - Advanced Regression Techniques
Participation in the Kaggle competition "House Prices - Advanced Regression Techniques," utilizing regression models to predict house prices.
📺 **Video Walkthrough:** [YouTube Link](https://youtu.be/-jZjGtT4hqQ)
### 4. Pandas Library
Exploring the Pandas library for data manipulation, including data cleaning, aggregation, and transformation techniques.
📺 **Video Walkthrough:** [YouTube Link](https://youtu.be/09iK47ARspg)
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### 🔧 Technologies Used
- Python
- NumPy
- Pandas
- Matplotlib
- Scikit-Learn
Feel free to explore the repository and check out the linked videos for detailed explanations! 🚀