This repository curates a comprehensive list of guided projects for individuals looking to build a portfolio in data science and AI. It covers Large Language Models (LLMs), time series analysis, computer vision, and general data science applications, providing practical, hands-on learning opportunities.

How It Works

The repository acts as a directory, linking to various guided projects that often involve popular libraries and frameworks like Langchain, Hugging Face Transformers, PyCaret, and TensorFlow/PyTorch. The projects are categorized by domain, allowing users to focus on specific areas of AI and data science.

Quick Start & Requirements

This is a curated list, not a runnable project. To follow the guided projects, users will need to set up individual project environments, which typically require Python, relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers), and potentially cloud services (AWS, Azure) or specific hardware (GPUs) depending on the project's complexity. Links to specific project tutorials or codebases are often provided within the descriptions.

Highlighted Details

• Extensive coverage of LLM projects, including chatbot development, fine-tuning (LoRA, QLoRA, Autotrain), and deployment.
• Detailed sections on time series analysis and forecasting with tools like Prophet, Neural Prophet, and XGBoost.
• A wide array of computer vision projects, from facial recognition and sign language detection to object detection and image classification.
• Includes projects focused on practical data science applications like salary prediction, real estate pricing, and recommender systems.

Maintenance & Community

This is a community-curated list. Maintenance and updates depend on contributions from the open-source community. There are no specific community links or contributor details provided in the README.

Licensing & Compatibility

The repository itself is a list and does not have a specific license. Individual projects linked within the repository will have their own licenses, which users must adhere to.

Limitations & Caveats

As a curated list, the repository does not provide direct code execution or unified setup. Users must independently set up and manage the environments for each individual project they choose to pursue. The quality and maintenance of linked projects can vary.