Neural Breakdown with AVB Courses

Training Small Language Models to Reason with Reinforcement Learning - GRPO from Scratch

Master GRPO algorithm implementation from scratch to train small language models for reasoning using reinforcement learning with PyTorch code and policy gradient techniques.

• YouTube
• 51 minutes
• Self-Paced
• Free Video

Best NLP, Transformers, and LLM Research Papers of 2024 - A Comprehensive Review

Explore groundbreaking developments in LLM research through a curated analysis of 2024's most influential papers, covering tokenization, RNN revival, Mamba architecture, and advanced prompting techniques.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Byte Latent Transformers - Understanding Meta's BLT Model for Efficient Language Processing

Dive into Meta's Byte Latent Transformers (BLT) architecture, exploring how this innovative approach uses byte-level processing and dynamic compute allocation to enhance language model efficiency and performance.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Evolution of Transformer Architectures - From Attention to Modern Variants

Explore the evolution of neural attention mechanisms, from basic self-attention to advanced concepts like Multi Query and Grouped Query Attention, with clear visualizations and practical insights.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

The 6 Questions That Every Reinforcement Learning Algorithm Must Answer

Discover the 6 fundamental questions every RL algorithm must answer, covering Q-learning, policy gradients, actor-critics, and model-based approaches in a clear framework.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Diffusion Language Models vs Autoregressive Language Models - Complete Gemini Diffusion Breakdown

Explore the differences between diffusion and autoregressive language models, focusing on Google Gemini's approach, training methods, and comparative advantages over traditional GPT models.

• YouTube
• 17 minutes
• Self-Paced
• Free Video

How to Build Multi-lingual Voice Apps in Python with Sarvam.AI - Hands-on Tutorial

Master building 4 multilingual AI voice apps with Sarvam.AI: chatbots with memory, speech-to-speech conversion, task managers using MCP, and YouTube RAG QA systems.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

Exploration in Sparse RL Environments - Curiosity and Random Network Distillation (RND)

Explore self-supervised exploration methods in reinforcement learning with Curiosity and Random Network Distillation (RND), learning how these techniques help agents navigate sparse environments through Python and PyTorch implementations.

• YouTube
• 23 minutes
• Self-Paced
• Free Video

PyTorch Tutorial - 7 Essential Concepts for Deep Learning

Master PyTorch fundamentals through 7 key concepts covering tensors, automatic differentiation, neural networks, and advanced architectures like CNNs and transformers.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

Context Engineering with DSPy - Comprehensive Hands-On Course for Building LLM Applications

Master DSPy for building reliable LLM applications with RAG, multi-agent systems, tool calling, and advanced context engineering techniques in this comprehensive hands-on guide.

• YouTube
• 1 hour 22 minutes
• Self-Paced
• Free Video

Best Computer Vision Research Papers of 2024 - A Comprehensive Analysis

Explore groundbreaking advances in computer vision through 12 influential research papers covering video diffusion, image generation, depth estimation, and object detection technologies.

• YouTube
• 17 minutes
• Self-Paced
• Free Video

Visually Explaining Mixture of Experts LLMs like DeepSeek and Mixtral - How to Code

Dive into the visual explanation of Mixture of Experts (MOE) Transformers powering modern LLMs like DeepSeek and Mixtral, covering key concepts from routing mechanisms to expert capacity with code examples.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

Sesame AI and RVQs - The Network Architecture Behind Viral Speech Models

Explore the architecture of Sesame Conversational Speech Model, including Mimi Encoder tokenization with split RVQ, semantic and acoustic codes, and the Autoregressive Transformer Backbone that enables natural speech interaction.

• YouTube
• 19 minutes
• Self-Paced
• Free Video

Building Awesome Speech-to-Text Transformers from Scratch - One Line of PyTorch at a Time

Master building a Speech-to-Text model from scratch with PyTorch, including convolutional layers, transformers, vector quantization, and CTC loss for audio transcription.

• YouTube
• 53 minutes
• Self-Paced
• Free Video

10 Simple Tools for Building LLM Apps with Python Code Examples

Discover 10 essential Python tools for building industry-standard LLM applications, from structured outputs with PydanticAI to deployment strategies, with practical code examples.

• YouTube
• 19 minutes
• Self-Paced
• Free Video