{"id":6055,"date":"2024-01-09T07:44:58","date_gmt":"2024-01-09T06:44:58","guid":{"rendered":"https:\/\/edihadria.eu\/?page_id=6055"},"modified":"2024-10-21T16:36:36","modified_gmt":"2024-10-21T14:36:36","slug":"razvoj-aplikacija-s-llm-om","status":"publish","type":"page","link":"https:\/\/edihadria.eu\/en\/razvoj-aplikacija-s-llm-om\/","title":{"rendered":"Application development with LLM"},"content":{"rendered":"
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Education for IT industry<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\tApplication development with LLM\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tIntroduction to the development of applications using LLM (large language models). Examples of using LLM in various business applications and tasks. Transformers principles of operation. Learning principles of large language models for text generation. Learning and fine-tuning LLMs. Evaluation of LLMs. Benchmark data for evaluation. \t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t
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Content of the training:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\tApplication development project based on LLM. Phases and activities. Techniques for application development based on large language models: Prompt engineering. Fine-tuning. Castastrophic forgetting. Parameter efficient fine-tuning-PEFT and Low-Rank Adaptation of Large Language Models- LoRA techniques. Learning from human feedback and Reinforcement learning with human feedback RLHF. Retrieval Augmented Generation (RAG). Vector bases. Search vector databases. LLM agents. Construction of LLM applications- LangChain. Hardware requirements. Quantification of the grid parameter. Risks and limitations of generative AI. Bias and hallucinations. The difference between using pre-trained and fine-tuned models. Responsible use of AI and impact on society. The safety of using generative AI. \n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Duration: 5h<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Prof. dr. sc. Sanda Martin\u010di\u0107-Ip\u0161i\u0107, Faculty of Informatics and Digital Technologies Rijeka<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Location: Faculty of Informatics and Digital Technologies Rijeka, Hall 357, Radmile Matej\u010di\u0107 2, Rijeka; online<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Term: 17.04.2024, from 2 p.m. to 7 p.m.<\/p>
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Log in<\/a><\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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List of trainings:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Employee onboarding \u2013 what, how and when to do<\/a><\/p>

Upskilling<\/a><\/p>

Predictive analytics and the use of simple machine learning methods to predict market prices<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Opportunity for business transformation with generative AI<\/a><\/p>

Application of computer vision and deep learning to increase security and surveillance of the area<\/a><\/p>

Computer vision and deep learning: Application options and challenges<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Application development with LLM<\/a><\/p>

Text analysis technologies<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t<- return<\/a><\/span>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

Training title Application development with LLMIntroduction to the development of applications using LLM (large language models). Examples of LLM usage in various business applications and tasks. Transformers principles of work. The principles of learning large language models to generate text. Learning and fine tuning of LLM. Evaluation of LLMs. Benchmark data for evaluation. Content of the training: Application development project based on LLM. Stages [...]<\/p>","protected":false},"author":14,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"footnotes":""},"class_list":["post-6055","page","type-page","status-publish","hentry"],"yoast_head":"\nRazvoj aplikacija s LLM-om<\/title>\n<meta name=\"description\" content=\"EDIH Adria (European Digital Innovation HUB), projekt financiran iz programa Digitalna Europa i Nacionalnog plana oporavka i otpornosti \u010diji je glavni cilj omogu\u0107avanje malim poduzetnicima i jedinicama lokalne samouprave ubrzanje procesa digitalizacije njihovih organizacija, pospje\u0161ivanje inovacijskog procesa, stvaranje prilika za testiranje ideja i rje\u0161enja prije po\u010detka investicijskog procesa.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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