Roadmaps for Machine Learning, Mathematics for Machine Learning, Python for ML, DS and DA, SQL for DS and DA
In this repository, you'll find comprehensive roadmaps covering:
- Machine Learning: Fundamental concepts, algorithms, and applications in the field.
- Mathematics for Machine Learning: Key mathematical concepts, including linear algebra, calculus, probability, and statistics.
- Python for Machine Learning, Data Science and Data Analyst: Essential Python libraries, tools, and best practices for building ML models.
- SQL for Data Science and Data Analyst: Understanding how to query and manipulate data using SQL.
Each roadmap will include:
- Learning Objectives: Clear goals to achieve by the end of each topic.
- Recommended Resources: Curated list of books, online courses, tutorials, and articles.
- Hands-on Projects: Practical exercises and projects to reinforce your learning.
- Additional Resources: Links to relevant tools, datasets, and communities.
- Explore the Roadmaps: Navigate through the directories to find roadmaps that interest you.
- Follow the Learning Paths: Each roadmap is designed to guide you step-by-step through the material.
- Engage with the Community: Feel free to contribute by sharing additional resources, suggesting improvements, or providing feedback.
Contributions are welcome! If you have resources, insights, or suggestions to improve the roadmaps, please create an issue or submit a pull request.
This repository is open-source and available under the MIT License.
For any questions or suggestions, please reach out via the Issues section.
Happy learning!