Welcome to the repository for the course! This repo contains all code, resources, and documentation to help you learn everything from Python basics to advanced data science and machine learning concepts.
- Introduction to Python
- Data Analysis with Python
- Data Visualization
- Statistics & Probability
- Machine Learning Algorithms
- Deep Learning
- Model Evaluation & Deployment
- Real-world Projects
- Getting Started
- Course syllabus
- Installation guide
- Python Fundamentals
- Numpy, Pandas, Matplotlib, Seaborn
- Exploratory Data Analysis
- Data cleaning
- Visualization techniques
- Statistics & Probability
- Descriptive statistics
- Inferential statistics
- Machine Learning
- Supervised learning (Regression, Classification)
- Unsupervised learning (Clustering, Dimensionality Reduction)
- Model selection & evaluation
- Deep Learning
- Neural networks
- TensorFlow & Keras basics
- Projects
- End-to-end ML projects
- Kaggle competitions
- Deployment
- Model serving
- Using Flask/FastAPI
- Clone the repo:
git clone https://github.com/IbrahimBagwan1/ds-ml.git - Follow the modules in order.
- Refer to the
/notebooksfolder for Jupyter notebooks. - Check
/projectsfor hands-on assignments.
Contributions are welcome! Please open issues or submit pull requests for improvements.
This project is licensed under the MIT License.
Happy Learning!
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