Welcome to AI and Data Science Playground, a curated collection of 30+ end-to-end projects across Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Generative AI (GenAI), and Data Science.
This repository is designed to showcase hands-on experimentation, problem-solving, and practical applications in AI and Data Science.
This repository serves as a comprehensive portfolio of AI and Data Science projects, covering the entire workflow from data collection to modeling and insights.
Each project is structured to include:
- Problem Statement – the goal or question being solved
- Exploratory Data Analysis (EDA) – understanding the data with visualizations
- Data Preprocessing & Feature Engineering – cleaning and transforming data for modeling
- Model Building & Evaluation – applying ML/DL/NLP/GenAI methods with performance metrics
- Conclusions & Insights – actionable takeaways or recommendations
- Programming Languages: Python, SQL
- Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-Learn, TensorFlow, Keras, NLTK, spaCy, Hugging Face Transformers and many more!
- Tools & Platforms: Jupyter Notebook, Google Colab, VS Code
- Version Control: Git & GitHub
Projects in this repository are organized by domain/category, making it easy to navigate:
| Category | Examples of Techniques |
|---|---|
| Machine Learning (ML) | Regression, Classification, Clustering, Feature Engineering |
| Deep Learning (DL) | CNNs, RNNs, Autoencoders, GANs |
| Natural Language Processing (NLP) | Text Preprocessing, Sentiment Analysis, Text Classification, Transformers |
| Generative AI (GenAI) | Text Generation, Image Generation, GANs, Diffusion Models |
| Data Science & Analytics | EDA, Dashboards, Visualization, Insights |
Each project folder contains the notebook, data (if allowed), and supporting files.
- Clone the repository
git clone https://github.com/babaralimahar/AI-and-Data-Science-Playground.git