{"id":18819846,"url":"https://github.com/adi3042/data_science","last_synced_at":"2026-01-17T06:30:16.034Z","repository":{"id":175851343,"uuid":"654581316","full_name":"Adi3042/Data_Science","owner":"Adi3042","description":"📊🚀 Explore the Data Science Universe!  Unlock insights and master data skills with hands-on assignments spanning machine learning, visualization, and more. 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🌟 This repository is a comprehensive collection of assignments and projects that cover essential data science topics, powered by Python and its powerful libraries.\n\n### Table of Contents\n\n1. **Python Fundamentals**: Start with the basics of Python programming, the backbone of data science.\n2. **Pandas \u0026 NumPy**: Harness the power of these libraries for data manipulation and numerical operations.\n3. **Machine Learning**: Implement various ML algorithms using libraries like Scikit-learn.\n4. **Natural Language Processing**: Dive into NLP tasks with libraries such as NLTK and SpaCy.\n5. **Computer Vision**: Explore image processing and recognition using OpenCV and TensorFlow.\n6. **Deep Learning**: Build neural networks with TensorFlow and Keras.\n7. **Clustering**: Apply clustering algorithms for unsupervised learning.\n8. **Data Visualization**: Create insightful visualizations using Matplotlib, Seaborn, and Plotly.\n9. **Statistical Analysis**: Perform statistical methods and inference using SciPy and Statsmodels.\n10. **Dimensionality Reduction**: Simplify datasets while retaining information using PCA and t-SNE.\n11. **Anomaly Detection**: Identify outliers and unusual patterns with Isolation Forest and other techniques.\n12. **Model Deployment**: Learn to deploy models using Flask, Docker, and cloud services like AWS.\n13. **Time Series Analysis**: Analyze and forecast time-based data using ARIMA and Prophet.\n14. **Big Data Processing**: Work with large datasets using PySpark and Dask.\n15. **Data Cleaning \u0026 Preprocessing**: Prepare raw data for analysis with Pandas and Scikit-learn.\n16. **Feature Engineering**: Enhance models with meaningful features using Python's ecosystem.\n\n### Ready to Explore?\n\nThis repository is your gateway to mastering data science with Python. Dive into these hands-on challenges, experiment, and elevate your skills. Happy coding! 🚀\n\n---\n\nThis version incorporates Python and relevant libraries, emphasizing their importance in your data science journey.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadi3042%2Fdata_science","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadi3042%2Fdata_science","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadi3042%2Fdata_science/lists"}