Embarking on the Future of AI Product Development

Learn the technology concepts needed to build modern AI applications. From document processing to embeddings and vectors and all the way to integrating with LLMs, find code and explanations here.

In a rapidly evolving technological landscape, the potential of Artificial Intelligence (AI) is undeniably profound. From simple automations to intricate neural networks simulating human cognition, AI has integrated itself into nearly every facet of modern life.

However, its incorporation into product development is an art few have mastered—until now.

Enter "AI Unveiled" by Harsh Singhal, an engaging expedition into the realm of AI app development. Designed for learners at all stages—whether you're a novice just venturing into AI or a seasoned developer looking to hone your expertise—this material provides a step-by-step approach to building versatile AI applications.

Journey Through the Content:

  1. Processing PDF Documents: Kickstart your AI development journey by delving deep into PDF content extraction. Understand the intricacies of PDF data and master the art of processing it.
  2. Search with SQLite: Dive into the world of databases with SQLite. Store the content you’ve extracted from PDFs efficiently and master the power of full-text search.
  3. Search with Nearest Neighbors: Transition from text to numeric with Vector Embeddings. Discover the magic of transforming textual data into vectors and utilize Nearest Neighbor algorithms in scikit-learn to find similar vector representations.
  4. Approximate Nearest Neighbors: Take a leap with Annoy, a brainchild of Spotify, and delve into the scalable domain of approximate Nearest Neighbor algorithms. Explore the vastness of vector search and its potential applications.
  5. FastAPI Service: Step into the digital realm with web services using FastAPI. Build robust, scalable, and efficient web services, ready to be deployed in the vast expanse of the cloud.
  6. Deploy with Docker: Simplify your deployment process with Docker. Learn to craft an all-encompassing Docker image, ensuring your AI solutions are both versatile and accessible, regardless of the environment.
  7. Retrieval Augmented Generation: As a grand finale, immerse yourself in the revolutionary concept of RAG. Build on your accumulated knowledge and integrate the prowess of ChatGPT 3.5, a cutting-edge model from OpenAI, to create a comprehensive RAG solution from scratch.

"AI Unveiled" isn’t just a guide; it’s a beacon for all AI enthusiasts and developers. With its comprehensive content, it promises to illuminate the path of AI product development, making the journey as enlightening as the destination.

For those ready to redefine the boundaries of AI, your transformative journey begins here.

toc.md · main · Harsh Singhal / AI Product Development - Unleashing FastAPI and LLM in Python · GitLab

Happy coding and exploring!