https://github.com/adi3042/data_science

📊🚀 Explore the Data Science Universe! Unlock insights and master data skills with hands-on assignments spanning machine learning, visualization, and more. Your journey to becoming a data expert starts here! 🎯💡 DataScienceJourney
https://github.com/adi3042/data_science

anomaly-detection big-data-processing classification clustering computer-vision data-cleaning-and-preprocessing data-visualization deep-learning dimensionality-reduction ensemble-learning exploratory-data-analysis feature-engineering machine-learning model-deployment model-selection-and-evaluation natural-language-processing regression-analysis statistical-analysis time-series-analysis-and-forecasting

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📊🚀 Explore the Data Science Universe! Unlock insights and master data skills with hands-on assignments spanning machine learning, visualization, and more. Your journey to becoming a data expert starts here! 🎯💡 DataScienceJourney

• Host: GitHub
• URL: https://github.com/adi3042/data_science
• Owner: Adi3042
• License: mit
• Created: 2023-06-16T12:50:46.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-08-23T08:07:04.000Z (3 months ago)
• Last Synced: 2024-08-23T09:25:53.257Z (3 months ago)
• Topics: anomaly-detection, big-data-processing, classification, clustering, computer-vision, data-cleaning-and-preprocessing, data-visualization, deep-learning, dimensionality-reduction, ensemble-learning, exploratory-data-analysis, feature-engineering, machine-learning, model-deployment, model-selection-and-evaluation, natural-language-processing, regression-analysis, statistical-analysis, time-series-analysis-and-forecasting
• Language: Jupyter Notebook
• Homepage:
• Size: 4.63 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
## Data Science Assignments

Welcome to my data science journey! 🌟 This repository is a comprehensive collection of assignments and projects that cover essential data science topics, powered by Python and its powerful libraries.

### Table of Contents

1. **Python Fundamentals**: Start with the basics of Python programming, the backbone of data science.

2. **Pandas & NumPy**: Harness the power of these libraries for data manipulation and numerical operations.

3. **Machine Learning**: Implement various ML algorithms using libraries like Scikit-learn.

4. **Natural Language Processing**: Dive into NLP tasks with libraries such as NLTK and SpaCy.

5. **Computer Vision**: Explore image processing and recognition using OpenCV and TensorFlow.

6. **Deep Learning**: Build neural networks with TensorFlow and Keras.

7. **Clustering**: Apply clustering algorithms for unsupervised learning.

8. **Data Visualization**: Create insightful visualizations using Matplotlib, Seaborn, and Plotly.

9. **Statistical Analysis**: Perform statistical methods and inference using SciPy and Statsmodels.

10. **Dimensionality Reduction**: Simplify datasets while retaining information using PCA and t-SNE.

11. **Anomaly Detection**: Identify outliers and unusual patterns with Isolation Forest and other techniques.

12. **Model Deployment**: Learn to deploy models using Flask, Docker, and cloud services like AWS.

13. **Time Series Analysis**: Analyze and forecast time-based data using ARIMA and Prophet.

14. **Big Data Processing**: Work with large datasets using PySpark and Dask.

15. **Data Cleaning & Preprocessing**: Prepare raw data for analysis with Pandas and Scikit-learn.

16. **Feature Engineering**: Enhance models with meaningful features using Python's ecosystem.

### Ready to Explore?

This repository is your gateway to mastering data science with Python. Dive into these hands-on challenges, experiment, and elevate your skills. Happy coding! 🚀

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This version incorporates Python and relevant libraries, emphasizing their importance in your data science journey.