This is a description of a teaching experience. You can use markdown like any other post.

Welcome to the Rohit’s GenAI Nexus

GenAI, short for Generative Artificial Intelligence, is a fascinating field at the intersection of artificial intelligence and creativity. Whether you’re a beginner looking to understand the basics or an advanced learner diving deep into intricate concepts, this knowledge hub is your go-to resource.

Introduction

In the field of AI, generative models have gained immense popularity for their ability to create new content, ranging from images and text to music and even entire virtual worlds. GenAI techniques leverage neural networks to generate novel and realistic outputs, pushing the boundaries of what machines can accomplish.

Roadmap to GenAi Learning

• GenAI Foundational Concepts
  • GenAI Basics
• LLMs Cm oncepts
  • LLM Basics
  • What is Attention?
  • Transformers Architecture
  • Generative Pre-trained Transformers(GPT)
  • How GPTs are Trained
  • Reinforcement Learning
  • Bidirectional Encoder Representations from Transformers(BERT)
• Retrieval-Augmented-Generation(RAG)
  • RAG Intro
• GenAI-Techniques
  • Generative-Adversarial-Network(GAN)
  • Variational-Autoencoder(VAE)
  • Difference between GANs and VAEs
  • Diffusion and Autoregressive Models
  • Mode Collapse and Mode Dropping
• Fine Tuning
  • FineTuning-Basics
  • Low Rank Adaptation(LoRA)
  • Quantized LLMs
  • 1 bit LLMs
• Evaluation of Generative AI models
• Generative AI Ethics
• Generative AI Deployment

Get Started

Choose a topic from the table of contents above to begin your exploration of GenAI. Happy learning!