Continue your exploration of Large Language Models (LLMs) with Andreea Turcu's foundational Level 2 course! Specially designed for those with foundational knowledge, this course delves deep into optimizing Natural Language Processing (NLP) models through robust data practices. Discover the critical role of clean data and effective data preparation techniques essential for NLP model quality. Using LLM DataStudio, navigate supported workflows, customize interfaces, and implement quality control measures. Learn to set up projects and leverage collaboration features to enhance team efficiency. Master QnA dataset creation, ensuring accuracy through validation and quality assurance processes. Perfect fine-tuning with H2O LLM Studio, where you'll tailor models to specific tasks. Explore workflows, employ data augmentation strategies, and select optimal architectures from pre-trained models. Delve deeper into advanced techniques like Quantisation and LoRA for model compression, optimizing your NLP applications for real-world deployment. Earn your LLM Certification Level 2, showcasing your expertise in data preparation, fine-tuning, and model optimization. This certification is ideal for professionals that are aiming to excel in specialized roles within NLP, machine learning, and data engineering. Join Andreea Turcu in this course and elevate your skills in harnessing LLMs for cutting-edge NLP projects, where you鈥檒l dive into practical applications of language models and supercharge your AI career!
Deploying LLM Models with H2O LLM Studio
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Skills You'll Learn
Data Cleansing, Data Quality, MLOps (Machine Learning Operations), Data Validation, Natural Language Processing, Performance Tuning, User Interface (UI), Data Processing, Feature Engineering, Data Transformation, Verification And Validation, Large Language Modeling, Collaborative Software
From the lesson
Fine-Tuning Your Large Language Models
Taught By
Andreea Turcu
Head of Global Training