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feat: ajouter des sections de projets et des outils dans ArtStudies, et enregistrer une nouvelle invite pour récupérer les projets d'Arthur Danjou
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@@ -42,7 +42,11 @@ The projects are organized into two main sections:
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- `Statistical Learning`
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- `Statistical Learning`
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- `M2`
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- `M2`
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- `Data Visualisation`
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- `Deep Learning`
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- `Linear Models`
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- `Machine Learning`
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- `Machine Learning`
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- `VBA`
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- `SQL`
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- `SQL`
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## 🛠️ Technologies & Tools
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## 🛠️ Technologies & Tools
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@@ -55,10 +59,12 @@ The projects are organized into two main sections:
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- [SciPy](https://www.scipy.org): A library for advanced scientific computations including optimization, integration, and signal processing.
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- [SciPy](https://www.scipy.org): A library for advanced scientific computations including optimization, integration, and signal processing.
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- [Scikit-learn](https://scikit-learn.org): A robust library offering simple and efficient tools for machine learning and statistical modeling, including classification, regression, and clustering.
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- [Scikit-learn](https://scikit-learn.org): A robust library offering simple and efficient tools for machine learning and statistical modeling, including classification, regression, and clustering.
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- [TensorFlow](https://www.tensorflow.org): A comprehensive open-source framework for building and deploying machine learning and deep learning models.
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- [TensorFlow](https://www.tensorflow.org): A comprehensive open-source framework for building and deploying machine learning and deep learning models.
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- [Keras](https://keras.io): A high-level neural networks API, running on top of TensorFlow, designed for fast experimentation.
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- [Matplotlib](https://matplotlib.org): A versatile plotting library for creating high-quality static, animated, and interactive visualizations in Python.
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- [Matplotlib](https://matplotlib.org): A versatile plotting library for creating high-quality static, animated, and interactive visualizations in Python.
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- [Plotly](https://plotly.com): An interactive graphing library for creating dynamic visualizations in Python and R.
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- [Plotly](https://plotly.com): An interactive graphing library for creating dynamic visualizations in Python and R.
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- [Seaborn](https://seaborn.pydata.org): A statistical data visualization library built on top of Matplotlib, providing a high-level interface for drawing attractive and informative graphics.
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- [Seaborn](https://seaborn.pydata.org): A statistical data visualization library built on top of Matplotlib, providing a high-level interface for drawing attractive and informative graphics.
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- [RMarkdown](https://rmarkdown.rstudio.com): A dynamic tool for combining code, results, and narrative into high-quality documents and presentations.
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- [RMarkdown](https://rmarkdown.rstudio.com): A dynamic tool for combining code, results, and narrative into high-quality documents and presentations.
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- [FactoMineR](https://factominer.free.fr/): An R package focused on multivariate exploratory data analysis (e.g., PCA, MCA, CA).
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- [FactoMineR](https://factominer.free.fr/): An R package focused on multivariate exploratory data analysis (e.g., PCA, MCA, CA).
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- [ggplot2](https://ggplot2.tidyverse.org): A grammar-based graphics package for creating complex and elegant visualizations in R.
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- [ggplot2](https://ggplot2.tidyverse.org): A grammar-based graphics package for creating complex and elegant visualizations in R.
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- [RShiny](https://shiny.rstudio.com): A web application framework for building interactive web apps directly from R.
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- and my 🧠.
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- and my 🧠.
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@@ -300,6 +300,25 @@ function createServer() {
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}
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}
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)
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)
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server.registerPrompt(
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'artmcp-projects',
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{
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title: 'Get Projects Done by Arthur Danjou',
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description: 'Get a list of projects done by Arthur Danjou'
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},
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async () => {
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return {
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messages: [{
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role: 'user',
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content: {
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type: 'text',
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text: `Provide me a list of projects done by Arthur Danjou.`
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}
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}]
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}
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}
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)
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return server
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return server
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}
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}
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