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Found 6 papers, 0 papers with code
Automating the Training and Deployment of Models in MLOps by Integrating Systems with Machine Learning
This article introduces the importance of machine learning in real-world applications and explores the rise of MLOps (Machine Learning Operations) and its importance for solving challenges such as model deployment and performance monitoring.
Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology
In addition to environmental perception sensors such as cameras, radars, etc.
Maximizing User Experience with LLMOps-Driven Personalized Recommendation Systems
The integration of LLMOps into personalized recommendation systems marks a significant advancement in managing LLM-driven applications.
Research on the Application of Deep Learning-based BERT Model in Sentiment Analysis
This paper explores the application of deep learning techniques, particularly focusing on BERT models, in sentiment analysis.
Emerging Synergies Between Large Language Models and Machine Learning in Ecommerce Recommendations
With the boom of e-commerce and web applications, recommender systems have become an important part of our daily lives, providing personalized recommendations based on the user's preferences.
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models
In addressing the computational and memory demands of fine-tuning Large Language Models(LLMs), we propose LoRA-SP(Streamlined Partial Parameter Adaptation), a novel approach utilizing randomized half-selective parameter freezing within the Low-Rank Adaptation(LoRA)framework.
