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		<title>Projects on Clément</title>
		<link>https://clement.mariebrisson.fr/projects/</link>
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				<title>Bitcoin Cash ELT Pipeline</title>
				<link>https://clement.mariebrisson.fr/projects/bitcoin-cash-elt-pipeline/</link>
				<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
				<guid>https://clement.mariebrisson.fr/projects/bitcoin-cash-elt-pipeline/</guid>
				<description>&lt;h2 id=&#34;project-overview&#34;&gt;&#xD;&#xA;  Project overview&#xD;&#xA;  &lt;a class=&#34;heading-link&#34; href=&#34;#project-overview&#34;&gt;&#xD;&#xA;    &lt;i class=&#34;fa-solid fa-link&#34; aria-hidden=&#34;true&#34; title=&#34;Link to heading&#34;&gt;&lt;/i&gt;&#xD;&#xA;    &lt;span class=&#34;sr-only&#34;&gt;Link to heading&lt;/span&gt;&#xD;&#xA;  &lt;/a&gt;&#xD;&#xA;&lt;/h2&gt;&#xD;&#xA;&lt;p&gt;ELT pipeline transforming Bitcoin Cash blockchain data (BigQuery public data) with dbt Cloud, with a staging layer and a datamart layer.&lt;/p&gt;&#xA;&lt;p&gt;A CI/CD workflow with GitHub Actions automatically lints the SQL queries with SQLFluff, to keep the code quality consistent.&lt;/p&gt;</description>
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				<title>NEO4J Recommendation Engine</title>
				<link>https://clement.mariebrisson.fr/projects/neo4j-recommendation-engine/</link>
				<pubDate>Sat, 28 Jan 2023 00:00:00 +0000</pubDate>
				<guid>https://clement.mariebrisson.fr/projects/neo4j-recommendation-engine/</guid>
				<description>&lt;h2 id=&#34;project-overview&#34;&gt;&#xD;&#xA;  Project overview&#xD;&#xA;  &lt;a class=&#34;heading-link&#34; href=&#34;#project-overview&#34;&gt;&#xD;&#xA;    &lt;i class=&#34;fa-solid fa-link&#34; aria-hidden=&#34;true&#34; title=&#34;Link to heading&#34;&gt;&lt;/i&gt;&#xD;&#xA;    &lt;span class=&#34;sr-only&#34;&gt;Link to heading&lt;/span&gt;&#xD;&#xA;  &lt;/a&gt;&#xD;&#xA;&lt;/h2&gt;&#xD;&#xA;&lt;p&gt;Benchmark study of the Neo4j graph database management system, leveraging its powerful Graph Data Science library to develop a recommendation engine. The benchmark was conducted using a real-world dataset of 1.5 million beer reviews from Kaggle, providing a valuable use case for the technology.&lt;/p&gt;&#xA;&lt;p&gt;Similarity algorithms were written in Cypher, a practical application of the concepts of the Neo4j Certified Professional certification.&lt;/p&gt;</description>
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				<title>FastAPI Challenge</title>
				<link>https://clement.mariebrisson.fr/projects/fastapi-challenge/</link>
				<pubDate>Fri, 27 Jan 2023 00:00:00 +0000</pubDate>
				<guid>https://clement.mariebrisson.fr/projects/fastapi-challenge/</guid>
				<description>&lt;h2 id=&#34;project-overview&#34;&gt;&#xD;&#xA;  Project overview&#xD;&#xA;  &lt;a class=&#34;heading-link&#34; href=&#34;#project-overview&#34;&gt;&#xD;&#xA;    &lt;i class=&#34;fa-solid fa-link&#34; aria-hidden=&#34;true&#34; title=&#34;Link to heading&#34;&gt;&lt;/i&gt;&#xD;&#xA;    &lt;span class=&#34;sr-only&#34;&gt;Link to heading&lt;/span&gt;&#xD;&#xA;  &lt;/a&gt;&#xD;&#xA;&lt;/h2&gt;&#xD;&#xA;&lt;p&gt;Web application that utilizes the power of Python and the FastAPI framework. The application is deployed in a Docker container, ensuring optimal performance and scalability. The application features three distinct endpoints, each providing valuable functionality for the users.&lt;/p&gt;&#xA;&lt;p&gt;The first endpoint allows users to &lt;strong&gt;get&lt;/strong&gt; the number of times they have listened to a specific artist. It requires &lt;code&gt;user_id&lt;/code&gt; as input and returns the &lt;strong&gt;number of listens&lt;/strong&gt;.&lt;/p&gt;</description>
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				<title>French Gazole Prices Map</title>
				<link>https://clement.mariebrisson.fr/projects/french-gazole-prices-map/</link>
				<pubDate>Fri, 27 Jan 2023 00:00:00 +0000</pubDate>
				<guid>https://clement.mariebrisson.fr/projects/french-gazole-prices-map/</guid>
				<description>&lt;h2 id=&#34;project-overview&#34;&gt;&#xD;&#xA;  Project overview&#xD;&#xA;  &lt;a class=&#34;heading-link&#34; href=&#34;#project-overview&#34;&gt;&#xD;&#xA;    &lt;i class=&#34;fa-solid fa-link&#34; aria-hidden=&#34;true&#34; title=&#34;Link to heading&#34;&gt;&lt;/i&gt;&#xD;&#xA;    &lt;span class=&#34;sr-only&#34;&gt;Link to heading&lt;/span&gt;&#xD;&#xA;  &lt;/a&gt;&#xD;&#xA;&lt;/h2&gt;&#xD;&#xA;&lt;p&gt;Shiny application that utilizes advanced R programming techniques to gather and analyze critical data from French open data sources. The app retrieves real-time prices of &amp;ldquo;gazole&amp;rdquo; from across the entire country.&lt;/p&gt;&#xA;&lt;p&gt;The data is obtained in a compressed format and then processed through data manipulation techniques to extract valuable insights in the form of a JSON file.&lt;/p&gt;&#xA;&lt;p&gt;The application then employs data visualization techniques, using the Leaflet library, to provide an interactive and intuitive map-based interface, where users can easily identify the locations of gas stations and the corresponding prices, which are represented using a color-coded scale, ranging from low to high prices.&lt;/p&gt;</description>
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