Welcome to the Notes Repository! This collection is organized to help learners and practitioners in AI, Machine Learning, Deep Learning, Data Science, and related fields. Below is an overview of the main sections and their contents to help you navigate and make the most of these resources.

• AI & ML Notes
• Deep Learning Notes
• Gen AI Notes
• Hugging Face Transformers Notes
• Pandas Notes
• PyTorch Notes
• Scikit-learn Notes
• Tesseract OCR Bangla Notes
• Development Notes
• System Design

• Path: AI ML/ai-engineer-notes/
• Structure:
  • Beginner/, Intermediate/, Advanced/
  • Each level contains topic-wise markdown files (e.g., Data Handling, Deep Learning, NLP, MLOps, Ethics, etc.)
• Purpose: Step-by-step learning path for aspiring AI/ML engineers, from basics to advanced topics.

• Path: AI ML/deep-learning-notes/
• Structure:
  • Phase 1 - Foundations/, Phase 2 - Core Deep Learning/, Phase 3 - Advanced Concepts/, Phase 4 - Research and Deployment/
  • Each phase contains detailed notes on relevant subtopics (e.g., Linear Algebra, CNNs, RNNs, Transfer Learning, etc.)
• Purpose: Comprehensive guide to deep learning, suitable for both beginners and advanced learners.

• Path: AI ML/gen-ai-notes/
• Structure:
  • Beginner/, Intermediate/, Advanced/, Expert/
• Purpose: Notes and resources on Generative AI, including foundational concepts and advanced techniques.

• Path: AI ML/hugging-face-transformers-notes/
• Structure:
  • Beginner/, Intermediate/, Advanced/
• Purpose: Guides and examples for using Hugging Face Transformers for NLP and other tasks.

• Path: AI ML/pandas-notes/
• Structure:
  • Beginner/, Intermediate/, Advanced/
  • Includes cheatsheets and exercises.
• Purpose: Practical notes and exercises for mastering data analysis with pandas.

• Path: AI ML/pytorch-notes/
• Structure:
  • Beginner/
• Purpose: Introductory notes and guides for learning PyTorch.

• Path: AI ML/sklearn-notes/
• Structure:
  • 1 Beginner/, 2 Intermediate/, 3 Advanced/, 4 Expert Addons/
• Purpose: Structured notes for learning and mastering scikit-learn.

• Path: AI ML/tesseract-ocr-bangla-notes/
• Structure:
  • Phase 1 - Beginner - Fundamentals of OCR & Tesseract/
  • Phase 2 - Intermediate - Bengali Text Recognition & Python Integration/
  • Phase 3 - Advanced – Customization and Training Tesseract/
  • Phase 4 - Expert – Real-World Applications and Deployment/
• Purpose: End-to-end guide for working with Tesseract OCR, especially for Bengali text.

• Path: Development/
• Structure:
  • Backend/ (e.g., docker, nestjs, redis)
  • Frontend/
• Purpose: Notes and guides for backend and frontend development tools and frameworks.

• Path: System Design/
• Purpose: Notes and resources for learning system design concepts and best practices.

• Browse the relevant section based on your learning goals.
• Each topic is organized in markdown files for easy reading and searching.
• Use the README files within each subfolder for more detailed navigation.

Happy Learning! If you find these notes helpful, consider contributing or suggesting improvements.