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.
- Python Fundamentals: Start with the basics of Python programming, the backbone of data science.
- Pandas & NumPy: Harness the power of these libraries for data manipulation and numerical operations.
- Machine Learning: Implement various ML algorithms using libraries like Scikit-learn.
- Natural Language Processing: Dive into NLP tasks with libraries such as NLTK and SpaCy.
- Computer Vision: Explore image processing and recognition using OpenCV and TensorFlow.
- Deep Learning: Build neural networks with TensorFlow and Keras.
- Clustering: Apply clustering algorithms for unsupervised learning.
- Data Visualization: Create insightful visualizations using Matplotlib, Seaborn, and Plotly.
- Statistical Analysis: Perform statistical methods and inference using SciPy and Statsmodels.
- Dimensionality Reduction: Simplify datasets while retaining information using PCA and t-SNE.
- Anomaly Detection: Identify outliers and unusual patterns with Isolation Forest and other techniques.
- Model Deployment: Learn to deploy models using Flask, Docker, and cloud services like AWS.
- Time Series Analysis: Analyze and forecast time-based data using ARIMA and Prophet.
- Big Data Processing: Work with large datasets using PySpark and Dask.
- Data Cleaning & Preprocessing: Prepare raw data for analysis with Pandas and Scikit-learn.
- Feature Engineering: Enhance models with meaningful features using Python's ecosystem.
This repository is your gateway to mastering data science with Python. Dive into these hands-on challenges, experiment, and elevate your skills. Happy coding! 🚀
This version incorporates Python and relevant libraries, emphasizing their importance in your data science journey.