https://github.com/markoshb/my-data-science-learning-projects

Short but illustrative notebooks to showcase data-analysis in Python
https://github.com/markoshb/my-data-science-learning-projects

data-science matplotlib-pyplot pandas python pythorch scikit-learn tensorflow

Last synced: 3 months ago
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Short but illustrative notebooks to showcase data-analysis in Python

• Host: GitHub
• URL: https://github.com/markoshb/my-data-science-learning-projects
• Owner: MarkosHB
• Created: 2025-02-14T14:49:38.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-03-02T15:45:40.000Z (9 months ago)
• Last Synced: 2025-03-02T16:33:25.162Z (9 months ago)
• Topics: data-science, matplotlib-pyplot, pandas, python, pythorch, scikit-learn, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 209 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 🚀 My Data Science Learning Projects.

Welcome to my personal collection of hands-on data science projects! This repository showcases my journey exploring and mastering various data science concepts, tools, and techniques. 

🌟 Stay tuned as I continue to expand this repository with more exciting projects!

  

> [!Note] 

> Have a look at this repo about my [Machine Learning Subject](https://github.com/MarkosHB/Machine-Learning-Subject) wich contains even more projects written in R.

### 🌸 Iris Classification.

- 📄 [Notebook](https://github.com/MarkosHB/My-Data-Science-Learning-Projects/blob/main/iris/notebook.ipynb)

- 🛠️ **Technologies:** Pandas, PyTorch.

- 🧪 **Summary:** A classic classification problem using the Iris dataset to practice data manipulation, visualization, and building simple neural networks.

### 🩺 Diabetes Prediction.

- 📄 [Notebook](https://github.com/MarkosHB/My-Data-Science-Learning-Projects/blob/main/diabetes/notebook.ipynb)

- 🛠️ **Technologies:** Scikit-learn, TensorFlow.

- 🧪 **Summary:** Predicting the likelihood of diabetes using machine learning models, focusing on data preprocessing and model evaluation.

### 🧑‍⚕️ Breast Cancer.

- 📄 [Notebook](https://github.com/MarkosHB/My-Data-Science-Learning-Projects/blob/main/breast_cancer/notebook.ipynb)

- 🛠️ **Technologies:** Autokeras, Scikit-learn.

- 🧪 **Summary:** Automated approach to classify breast cancer cases. The project leverages AutoKeras to find optimal deep learning models with minimal manual tuning.

### 🍷 Wine.

- 📄 [Notebook](https://github.com/MarkosHB/My-Data-Science-Learning-Projects/blob/main/wine/notebook.ipynb)

- 🛠️ **Technologies:** Pyspark, Pandas.

- 🧪 **Summary:** The script processes the Wine dataset using Apache Spark, performing data cleaning, exploration, and applying custom pandas UDFs for additional transformations.

### 🏠 California Housing.

- 📄 [Notebook](https://github.com/MarkosHB/My-Data-Science-Learning-Projects/blob/main/california_housing/notebook.ipynb)

- 🛠️ **Technologies:** Dask, Scikit-learn.

- 🧪 **Summary:** This time, we will use an alternative to Pandas so that parallel computing is considered when manipulating dataframes thanks to the library Dask.

### 💭 Movie Reviews.

- 📄 [Notebook](https://github.com/MarkosHB/My-Data-Science-Learning-Projects/blob/main/movie_reviews/notebook.ipynb)

- 🛠️ **Technologies:** NLTK, Scikit-learn.

- 🧪 **Summary:** The notebook analyzes movie reviews using the NLTK library, focusing on text preprocessing, feature extraction, and sentiment classification with a Naive Bayes model.

### 📊 ManageYourData.

- 💻 [Repository](https://github.com/MarkosHB/ManageYourData)

- 🛠️ **Technologies:** Pandas, Matplotlib, FPDF, Openpyxl, Streamlit.

- 🧪 **Summary:** A self-made tool for generating PDF reports from data files locally.

---

### 🎛️ Data analysis.

- 📋 [Carprice report](https://github.com/MarkosHB/My-Data-Science-Learning-Projects/blob/main/carprice/carprice.pdf) and [Titanic report](https://github.com/MarkosHB/My-Data-Science-Learning-Projects/blob/main/titanic/titanic.pdf)

-  🛠️ **Technologies:** Power BI.

- 🧪 **Summary:** My first two dashboards ever made with Power BI allowed me to learn the basics of visualizing and manipulating data.