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Arthur DANJOU
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- Created a new article on "Understanding AI Agents, LLMs, and RAG" detailing the synergy between AI agents, LLMs, and Retrieval-Augmented Generation. - Added an introductory article on "What is Machine Learning?" covering types, model selection, workflow, and evaluation metrics. chore: setup ESLint and Nuxt configuration - Added ESLint configuration for code quality. - Initialized Nuxt configuration with various modules and settings for the application. chore: initialize package.json and TypeScript configuration - Created package.json for dependency management and scripts. - Added TypeScript configuration for the project. feat: implement API endpoints for activity and stats - Developed API endpoint to fetch user activity from Lanyard. - Created a stats endpoint to retrieve Wakatime coding statistics with caching. feat: add various assets and images - Included multiple images and assets for articles and projects. - Added placeholder files to maintain directory structure. refactor: define types for chat, lanyard, time, and wakatime - Created TypeScript types for chat messages, Lanyard activities, time formatting, and Wakatime statistics.
26 lines
1.0 KiB
Markdown
26 lines
1.0 KiB
Markdown
---
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slug: monte-carlo-project
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title: 💻 Monte Carlo Methods Project
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description: A project to demonstrate the use of Monte Carlo methods in R.
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publishedAt: 2024/11/24
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readingTime: 3
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tags:
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- r
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- maths
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---
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This is the report for the Monte Carlo Methods Project. The project was done as part of the course `Monte Carlo Methods` at the Paris-Dauphine University. The goal was to implement different methods and algorithms using Monte Carlo methods in R.
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Methods and algorithms implemented:
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- Plotting graphs of functions
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- Inverse c.d.f. Random Variation simulation
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- Accept-Reject Random Variation simulation
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- Random Variable simulation with stratification
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- Cumulative density function
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- Empirical Quantile Function
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You can find the code here: [Monte Carlo Project Code](https://github.com/ArthurDanjou/Studies/blob/0c83e7e381344675e113c43b6f8d32e88a5c00a7/M1/Monte%20Carlo%20Methods/Project%201/003_rapport_DANJOU_DUROUSSEAU.rmd)
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<iframe src="/projects/monte-carlo-project/Report.pdf" width="100%" height="1000px">
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</iframe>
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