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Learn LLM Fine-Tuning, earn certificates with free online courses from Duke, IIM Bangalore and other top universities around the world. Read reviews to decide if a class is right for you.
Stay ahead of the web dev game by harnessing the power of AI. Build a movie pitch generator, a GPT-4 chatbot, and a fine-tuned bot trained on your own dataset.
Combine the power of Agentic AI, Generative AI, Prompt Engineering and Deep RL to build powerful AIs with AWS and Python
Design and Integrate AI-Powered S/LLMs into Enterprise Apps using Prompt Engineering, RAG, Fine-Tuning and Vector DBs
Fine-tune Falcon 7B with QLoRA on ecommerce support FAQs, then compare its responses before and after training.
Explore LLM fine-tuning techniques to reduce costs and improve performance. Learn to select base models, prepare datasets, run fine-tuning jobs, and evaluate results for specific AI tasks.
Master end-to-end LLM fine-tuning with W&B Models, from experiment tracking to model deployment in production. Learn to publish models, automate evaluations, and implement CI/CD workflows for efficient AI development.
Discover how Tinkr revolutionizes AI development through scalable architecture and real-world applications, empowering teams to build and deploy machine learning systems faster.
Explore LLM-as-judge techniques and instruction finetuning methods for supervised fine-tuning in this comprehensive data science presentation.
Learn how transformer-based LLMs work end to end: pre-training, empirical scaling laws, fine-tuning and evaluation, reinforcement learning, and deploying LLM-powered applications.
Build AI apps with OpenAI's JavaScript SDK: generate images with Dall-E, create a GPT-4 chatbot, fine-tune it on your own dataset, and deploy securely.
Build and deploy LLM-based NLP apps with Hugging Face transformers, PyTorch, RAG, and LangChain, covering tokenization, embeddings, attention, fine-tuning, and prompt engineering.
Personnalisez, déployez et évaluez des grands modèles de langage avec Amazon SageMaker JumpStart, notamment par le RAG, l’ingénierie de prompt et l’ajustement.
Amazon SageMaker JumpStartでLLMをカスタマイズ、デプロイ、評価し、RAGアプリケーションを構築する方法を学びます。
介紹以檢索增強生成與微調兩種技術最佳化基礎模型的方法,並涵蓋效能評估與微調資料準備。
Explora cómo mejorar modelos fundacionales mediante RAG, agentes para tareas de varios pasos y ajuste fino con datos preparados y métricas empresariales.
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