Introduction to Data Science

Welcome to the "Introduction to Data Science" repository! This collection is designed to provide beginners with hands-on experience in Data Science through a series of mini projects covering various essential topics.

What is Data Science?

Data Science is an interdisciplinary field that combines domain knowledge, statistics, programming, and machine learning to extract insights and knowledge from data. This repository aims to help aspiring Data Scientists get started on their learning journey by providing practical projects that apply fundamental Data Science concepts.

Main Topics

Machine Learning Fundamentals

• Classification
• Regression
• Clustering
• Dimensionality Reduction

Natural Language Processing (NLP)

• Sentiment Analysis
• Named Entity Recognition (NER)
• Language Translation
• Text Generation

Time Series Analysis

• Time Series Forecasting
• Trend Analysis
• Seasonality Analysis

Data Visualization and Storytelling

• Data Visualization Techniques
• Creating Interactive Visualizations
• Storytelling with Data

Deep Learning

• Neural Networks
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN)
• Transfer Learning

Model Evaluation and Deployment

• Model Evaluation Metrics
• Cross-Validation
• Model Deployment Techniques

Feature Engineering

• Feature Selection
• Feature Scaling
• Feature Transformation

Big Data and Spark

• Introduction to Big Data
• Distributed Data Processing with Apache Spark

Data Ethics and Bias

• Ethical Considerations in Data Science
• Addressing Bias in Data and Models

Advanced Topics

• Reinforcement Learning
• Generative Adversarial Networks (GANs)
• Autoencoders

Miscellaneous

• A/B Testing
• Imbalanced Data Handling
• Hyperparameter Tuning

Getting Started

To get started with a mini project, simply click on the corresponding links above to navigate to the respective project folder. Each folder contains the necessary code, data, and instructions to complete the mini project successfully.

Contribution

If you'd like to contribute to this repository by adding more mini projects or improving existing ones, feel free to submit a pull request. Your contributions are greatly appreciated!

Happy learning and exploring the exciting world of Data Science!