Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
This tutorial video delves into the innovative architecture of DeepSeek R1, explaining how it achieves exceptional reasoning capabilities through advanced reinforcement learning techniques. Explore the Group Relative Policy Optimization (GRPO) methodology and understand how it improves upon traditional PPO approaches for AI training. Discover the critical role of KL divergence in maintaining model stability, with practical code demonstrations and clear mathematical explanations throughout the 68-minute session. The comprehensive content covers the complete R1 development pathway, from initial supervised fine-tuning through reinforcement learning with neural reward models to final distillation. Gain insights into consistency rewards for Chain-of-Thought reasoning, data generation techniques, and detailed mathematical formulations with benchmarking results that demonstrate why these approaches lead to superior AI reasoning performance.
