My Courses
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A Hands-on Guide to PaliGemma 2 Vision Language Model
PaliGemma 2 redefines Vision-Language Models with unmatched versatility and precision. Explore its architecture, innovations, and real-world applications.
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DeepSeek-V3 Explained: Optimizing Efficiency and Scale
Explore how DeepSeek-V3 redefines AI with groundbreaking architecture, efficient training, and impactful real-world applications in coding, education, and multilingual systems.
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Top AI Research Papers of 2024
Discover the most influential AI research papers of 2024, featuring advancements like Mixtral, Byte Latent Transformer, and Movie Gen. Learn how these breakthroughs redefine efficiency, scalability, and real-world applications in artificial intelligence.
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Deep Dive into Byte Latent Transformer: Mastering Token-Free Efficiency
The Byte Latent Transformer (BLT) eliminates tokenization, learning directly from raw bytes. Explore its dynamic patching, scalable architecture, and revolutionary applications that set a new standard in efficiency and robustness.
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Attention-Based Distillation in LLMs: A Comprehensive Overview
Attention-Based Distillation efficiently compresses large language models by aligning attention patterns between teacher and student.
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Full Fine-Tuning vs. Parameter-Efficient Tuning: Trade-offs in LLM Adaptation
Choosing between full fine-tuning and parameter-efficient tuning depends on your task’s complexity and available resources. This guide helps you understand the trade-offs and make an informed decision for your LLM applications.
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Top Tools and Techniques for LLM Fine-Tuning: A Comprehensive Guide
Master LLM fine-tuning with tools, techniques, and practical insights for domain-specific AI applications.
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Mastering ModernBERT: The Evolution of Encoder Models
ModernBERT enhances BERT’s capabilities with longer context handling, optimized training techniques, and efficient inference.
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Deep Dive into LLaMA-Mesh: Mastering Text-to-3D Mesh Generation
LLaMA-Mesh bridges language and 3D design, enabling AI to generate 3D meshes from textual prompts. Explore its features, real-world applications in gaming, VR, and education, and its potential to revolutionize collaborative design workflows.
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All You Need to Know About Multi-Agent Reinforcement Learning
Multi-Agent Reinforcement Learning (MARL) enables multiple agents to interact and optimize outcomes in dynamic environments.
