A comprehensive collection of machine learning and web development resources from CodeSignal's learning paths, implemented in Jupyter notebooks.
This repository contains Jupyter notebooks covering various topics from CodeSignal's course paths (https://learn.codesignal.com/course-paths). Initially focused on machine learning, the project has expanded to include web development with Python.
- Machine Learning with Sklearn and TensorFlow
- AI Theory and Coding
- Dimensionality Reduction in Python
- Prompt Engineering
- TensorFlow Deep Dive
- Machine Learning in Trading (using $TSLA)
- Algorithms and Data Structures in Python
- AI Interviews - Software Design & Architecture
- Django for Back-End Development
- API Development with Python and Flask
- Redis Mastery with Python
- Practical Learning: Hands-on implementation of theoretical concepts
- Diverse Topics: Covers ML, AI, web development, and more
- Industry Relevance: Focuses on in-demand skills and technologies
- Open Source: Encourages collaboration and knowledge sharing
- Clone the repository
- Open the Jupyter notebooks
- Explore the markdown explanations and code examples
- Experiment with the code and adapt it to your projects
Contributions are welcome! Feel free to submit pull requests with improvements, additional exercises, or bug fixes.
This project is open-source and available under the MIT License.