Search Results for "LEARN"
Kaggle Competition Winner Reveals Stacking Strategy with cuML
Kaggle Grandmaster Chris Deotte shares insights on winning the April 2025 Kaggle competition using stacking with cuML, leveraging GPU acceleration for fast and efficient modeling.
NVIDIA's R²D²: Transforming Robotic Assembly with Advanced Manipulation Techniques
Explore NVIDIA's R²D² advancements in robotic assembly, leveraging AI and machine learning for enhanced adaptability and precision in contact-rich manipulation tasks.
Chainalysis Hexagate: Revolutionizing DeFi Security with Machine Learning
Chainalysis Hexagate leverages pattern recognition and machine learning to proactively identify and mitigate DeFi threats, flagging $402.1 million in risky assets in Q1 2025.
NVIDIA DALI Expands Data Processing Capabilities with New Features
NVIDIA DALI introduces new features enhancing data processing efficiency, offering seamless PyTorch integration, improved video processing, and optimized execution flow for deep learning applications.
NVIDIA RAPIDS Enhances Machine Learning with Zero-Code Acceleration and Performance Gains
NVIDIA's RAPIDS introduces zero-code acceleration for machine learning, boosts IO performance, and supports out-of-core XGBoost training, streamlining data science workflows.
NVIDIA's cuML Enhances Tree-Based Model Inference with Forest Inference Library
NVIDIA's cuML 25.04 introduces enhancements to the Forest Inference Library, boosting tree-based model inference performance with new features and optimizations.
GitHub Explores AI and ML: Insights and Best Practices
GitHub Blog delves into AI and ML, offering insights from engineers and thought leaders on concepts, techniques, and real-world applications.
NVIDIA's GR00T-Dreams Blueprint Revolutionizes Robot Learning with Synthetic Data
NVIDIA introduces the GR00T-Dreams blueprint, leveraging synthetic trajectory data to advance humanoid robot learning, enabling adaptation to new environments with minimal human input.
NVIDIA Enhances LLMOps for Efficient Model Evaluation and Optimization
NVIDIA introduces advanced LLMOps strategies to tackle challenges in large language model deployment, focusing on fine-tuning, evaluation, and continuous improvement, as demonstrated in collaboration with Amdocs.
NVIDIA Advances ML in Manufacturing with CUDA-X Data Science
NVIDIA leverages CUDA-X data science to optimize chip manufacturing workflows, addressing challenges like dataset imbalance and enhancing model performance.
Exploring Open Source Reinforcement Learning Libraries for LLMs
An in-depth analysis of leading open-source reinforcement learning libraries for large language models, comparing frameworks like TRL, Verl, and RAGEN.
DeepSWE: Revolutionizing Coding Agents with Open-Source Reinforcement Learning
DeepSWE-Preview, an advanced coding agent, sets new benchmarks in open-source AI with a 59% success rate on SWE-Bench-Verified, showcasing state-of-the-art performance using reinforcement learning.