Welcome to the ultimate repository of Data Science resources — a one-stop destination for everything from learning fundamentals to building real-world projects and preparing for interviews.
Whether you're just starting your data science journey or you're an experienced professional brushing up on skills, this curated collection is for you.
- Python for Data Science
- Numpy, Pandas, Matplotlib, Seaborn
- Statistics & Probability
- Descriptive stats, Hypothesis testing, Bayesian thinking
- Machine Learning
- Supervised, Unsupervised, and basic Deep Learning
- Data Wrangling
- Cleaning, transforming, and preparing data
- Math for Data Science
- Linear Algebra, Calculus, Probability
- Data Visualization
- Effective charts using Matplotlib, Plotly, Seaborn
- Beginner → Intermediate → Advanced Data Science
- ML & DL specialization tracks
- Career transition guide from other fields
- 🧾 Jupyter Notebooks with real datasets
- 🎯 Mini Projects (EDA, Classification, Regression, Clustering)
- 🔍 End-to-End Projects with business problems
- 🧪 Model Evaluation Techniques (AUC, F1, Precision, etc.)
- Frequently asked DS/ML interview questions
- Coding questions with solutions
- Resume tips & project showcase strategies
- Clone the repo
git clone https://github.com/your-username/data-science-resources.git