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<rss xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:podcast="https://podcastindex.org/namespace/1.0" xmlns:media="http://search.yahoo.com/mrss/" version="2.0"><channel><title>Civic Conversations</title><link>https://www.spreaker.com/podcast/civic-conversations--7062211</link><description><![CDATA[This podcast focuses on government, democracy, and the relationship between citizens and public institutions. It encourages thoughtful discussions about leadership, laws, and social responsibility. Perfect for listeners passionate about civic education and public engagement.]]></description><atom:link href="https://www.spreaker.com/show/7062211/episodes/feed" rel="self" type="application/rss+xml"/><language>en</language><category>Food</category><copyright>Copyright HAKKARI GOWENT FM</copyright><image><url>https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/blue_square_mic.jpg</url><title>Civic Conversations</title><link>https://www.spreaker.com/podcast/civic-conversations--7062211</link></image><lastBuildDate>Mon, 24 Aug 2026 02:03:00 +0000</lastBuildDate><itunes:author>HAKKARI GOWENT FM</itunes:author><itunes:owner><itunes:name>HAKKARI GOWENT FM</itunes:name><itunes:email>cemilkarabeg65@gmail.com</itunes:email></itunes:owner><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/blue_square_mic.jpg"/><itunes:subtitle>This podcast focuses on government, democracy, and the relationship between citizens and public institutions. It encourages thoughtful discussions about leadership, laws, and social responsibility. Perfect for listeners passionate about civic...</itunes:subtitle><itunes:summary><![CDATA[This podcast focuses on government, democracy, and the relationship between citizens and public institutions. It encourages thoughtful discussions about leadership, laws, and social responsibility. Perfect for listeners passionate about civic education and public engagement.]]></itunes:summary><itunes:category text="Arts"><itunes:category text="Food"/></itunes:category><itunes:explicit>false</itunes:explicit><podcast:guid>f20ce4ca-8bbc-5f57-965d-0b7143d7fc82</podcast:guid><itunes:type>episodic</itunes:type><item><title>Building Custom Graph Algorithms</title><link>https://www.spreaker.com/episode/building-custom-graph-algorithms--72293969</link><description><![CDATA[This podcast explores how developers can create custom graph algorithms using the Pregel API for large-scale graph processing and analytics. It discusses distributed computation, graph traversal techniques, and best practices for building scalable graph-based solutions. Perfect for software engineers, data scientists, graph database professionals, and anyone interested in advanced graph algorithm development.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72293969</guid><pubDate>Tue, 02 Jun 2026 10:45:08 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72293969/46_write_your_own_algorithms_using_the_pregel_api_dbhj9istgfq.mp3" length="42636567" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/86a053d9-8678-47ab-8eb9-18e594d2c888/86a053d9-8678-47ab-8eb9-18e594d2c888.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/86a053d9-8678-47ab-8eb9-18e594d2c888/86a053d9-8678-47ab-8eb9-18e594d2c888.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/86a053d9-8678-47ab-8eb9-18e594d2c888/86a053d9-8678-47ab-8eb9-18e594d2c888.vtt" type="text/vtt" language="en"/><itunes:author>HAKKARI GOWENT FM</itunes:author><itunes:subtitle>This podcast explores how developers can create custom graph algorithms using the Pregel API for large-scale graph processing and analytics. It discusses distributed computation, graph traversal techniques, and best practices for building scalable...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how developers can create custom graph algorithms using the Pregel API for large-scale graph processing and analytics. It discusses distributed computation, graph traversal techniques, and best practices for building scalable graph-based solutions. Perfect for software engineers, data scientists, graph database professionals, and anyone interested in advanced graph algorithm development.]]></itunes:summary><itunes:duration>2665</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/blue_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Smart Recommendations with Sparse Data</title><link>https://www.spreaker.com/episode/smart-recommendations-with-sparse-data--72293968</link><description><![CDATA[This podcast explores how graph-based recommendation systems can generate accurate suggestions even when data is limited or sparse. It discusses dimensionality reduction, graph analytics, and machine learning techniques used to uncover hidden relationships and improve recommendation quality. Perfect for data scientists, AI engineers, developers, and technology professionals interested in recommendation engines and connected data solutions.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72293968</guid><pubDate>Mon, 10 Jun 2024 15:30:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72293968/48_leveraging_dimensionality_for_graph_based_recommendations_with_sparse_data_qacseeekq0e.mp3" length="34122767" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/65b109e4-1750-4e77-8029-47448c4e1d54/65b109e4-1750-4e77-8029-47448c4e1d54.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/65b109e4-1750-4e77-8029-47448c4e1d54/65b109e4-1750-4e77-8029-47448c4e1d54.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/65b109e4-1750-4e77-8029-47448c4e1d54/65b109e4-1750-4e77-8029-47448c4e1d54.vtt" type="text/vtt" language="en"/><itunes:author>HAKKARI GOWENT FM</itunes:author><itunes:subtitle>This podcast explores how graph-based recommendation systems can generate accurate suggestions even when data is limited or sparse. It discusses dimensionality reduction, graph analytics, and machine learning techniques used to uncover hidden...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how graph-based recommendation systems can generate accurate suggestions even when data is limited or sparse. It discusses dimensionality reduction, graph analytics, and machine learning techniques used to uncover hidden relationships and improve recommendation quality. Perfect for data scientists, AI engineers, developers, and technology professionals interested in recommendation engines and connected data solutions.]]></itunes:summary><itunes:duration>2133</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/blue_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Bridging Divides Through Dialogue</title><link>https://www.spreaker.com/episode/bridging-divides-through-dialogue--72187100</link><description><![CDATA[In a world filled with differing opinions, respectful conversation has never been more important. In this episode, we discuss how empathy, listening, and constructive dialogue help bridge social and cultural divides. Explore how meaningful civic conversations can bring people together despite differences.<br /><br /><br /><br />]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72187100</guid><pubDate>Fri, 22 Dec 2023 15:28:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72187100/engineering_connections_across_deep_social_divides.mp3" length="16911183" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/e55269c0-5852-4717-8ad0-f8d24977594b/e55269c0-5852-4717-8ad0-f8d24977594b.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/e55269c0-5852-4717-8ad0-f8d24977594b/e55269c0-5852-4717-8ad0-f8d24977594b.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/e55269c0-5852-4717-8ad0-f8d24977594b/e55269c0-5852-4717-8ad0-f8d24977594b.vtt" type="text/vtt" language="en"/><itunes:author>HAKKARI GOWENT FM</itunes:author><itunes:subtitle>In a world filled with differing opinions, respectful conversation has never been more important. In this episode, we discuss how empathy, listening, and constructive dialogue help bridge social and cultural divides. Explore how meaningful civic...</itunes:subtitle><itunes:summary><![CDATA[In a world filled with differing opinions, respectful conversation has never been more important. In this episode, we discuss how empathy, listening, and constructive dialogue help bridge social and cultural divides. Explore how meaningful civic conversations can bring people together despite differences.<br /><br /><br /><br />]]></itunes:summary><itunes:duration>1057</itunes:duration><itunes:keywords>government</itunes:keywords><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/blue_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Graph-Powered Recommendations</title><link>https://www.spreaker.com/episode/graph-powered-recommendations--72293967</link><description><![CDATA[This podcast explores how graph structures can be used to uncover hidden relationships, predict missing information, and generate meaningful recommendations from complex datasets. Using wine and beverage data as a practical example, it discusses graph analytics, link prediction, and intelligent data enrichment techniques. Perfect for data scientists, AI practitioners, graph database enthusiasts, and anyone interested in discovering how connected data can solve real-world problems.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72293967</guid><pubDate>Fri, 20 Oct 2023 13:50:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72293967/45_beyond_the_wine_blend_using_graph_structures_to_fill_the_blanks_s_drxid8xp8.mp3" length="17307844" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/527b99a7-6c04-41d7-a505-50e07e6bbd3f/527b99a7-6c04-41d7-a505-50e07e6bbd3f.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/527b99a7-6c04-41d7-a505-50e07e6bbd3f/527b99a7-6c04-41d7-a505-50e07e6bbd3f.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/527b99a7-6c04-41d7-a505-50e07e6bbd3f/527b99a7-6c04-41d7-a505-50e07e6bbd3f.vtt" type="text/vtt" language="en"/><itunes:author>HAKKARI GOWENT FM</itunes:author><itunes:subtitle>This podcast explores how graph structures can be used to uncover hidden relationships, predict missing information, and generate meaningful recommendations from complex datasets. Using wine and beverage data as a practical example, it discusses graph...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how graph structures can be used to uncover hidden relationships, predict missing information, and generate meaningful recommendations from complex datasets. Using wine and beverage data as a practical example, it discusses graph analytics, link prediction, and intelligent data enrichment techniques. Perfect for data scientists, AI practitioners, graph database enthusiasts, and anyone interested in discovering how connected data can solve real-world problems.]]></itunes:summary><itunes:duration>1082</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/blue_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Real-Time Telemetry</title><link>https://www.spreaker.com/episode/real-time-telemetry--72293966</link><description><![CDATA[This podcast explores how Kafka, Neo4j, and real-time telemetry data can be combined to build powerful graph-based analytics systems. It discusses event streaming, connected data architectures, and techniques for capturing and analyzing live interactions from applications and games such as Doom. Perfect for data engineers, developers, cloud architects, and technology enthusiasts interested in real-time graph processing and streaming analytics.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72293966</guid><pubDate>Sat, 26 Aug 2023 01:10:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72293966/49_doom_kafka_and_neo4j_building_a_near_real_time_telemetry_graph_nbbxpakhg_i.mp3" length="44983432" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/6ac7e907-e490-4cb2-88a1-35d855cd3c97/6ac7e907-e490-4cb2-88a1-35d855cd3c97.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/6ac7e907-e490-4cb2-88a1-35d855cd3c97/6ac7e907-e490-4cb2-88a1-35d855cd3c97.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/6ac7e907-e490-4cb2-88a1-35d855cd3c97/6ac7e907-e490-4cb2-88a1-35d855cd3c97.vtt" type="text/vtt" language="en"/><itunes:author>HAKKARI GOWENT FM</itunes:author><itunes:subtitle>This podcast explores how Kafka, Neo4j, and real-time telemetry data can be combined to build powerful graph-based analytics systems. It discusses event streaming, connected data architectures, and techniques for capturing and analyzing live...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how Kafka, Neo4j, and real-time telemetry data can be combined to build powerful graph-based analytics systems. It discusses event streaming, connected data architectures, and techniques for capturing and analyzing live interactions from applications and games such as Doom. Perfect for data engineers, developers, cloud architects, and technology enthusiasts interested in real-time graph processing and streaming analytics.]]></itunes:summary><itunes:duration>2812</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/blue_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>How individual voices shape your community</title><link>https://www.spreaker.com/episode/how-individual-voices-shape-your-community--72187097</link><description><![CDATA[The provided text explores the fundamental pillars of a thriving society, emphasizing the necessity of active public participation. It suggests that robust communities are forged when individuals take an intentional role in influencing their surroundings. ]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72187097</guid><pubDate>Sat, 12 Aug 2023 12:50:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72187097/how_individual_voices_shape_your_community.mp3" length="14302700" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/fc04b21c-71eb-46c6-bc2d-c7b7ed154af0/fc04b21c-71eb-46c6-bc2d-c7b7ed154af0.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/fc04b21c-71eb-46c6-bc2d-c7b7ed154af0/fc04b21c-71eb-46c6-bc2d-c7b7ed154af0.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/fc04b21c-71eb-46c6-bc2d-c7b7ed154af0/fc04b21c-71eb-46c6-bc2d-c7b7ed154af0.vtt" type="text/vtt" language="en"/><itunes:author>HAKKARI GOWENT FM</itunes:author><itunes:subtitle>The provided text explores the fundamental pillars of a thriving society, emphasizing the necessity of active public participation. It suggests that robust communities are forged when individuals take an intentional role in influencing their...</itunes:subtitle><itunes:summary><![CDATA[The provided text explores the fundamental pillars of a thriving society, emphasizing the necessity of active public participation. It suggests that robust communities are forged when individuals take an intentional role in influencing their surroundings. ]]></itunes:summary><itunes:duration>894</itunes:duration><itunes:keywords>government</itunes:keywords><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/blue_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Embeddings &amp; Machine Learning</title><link>https://www.spreaker.com/episode/embeddings-machine-learning--72293970</link><description><![CDATA[This podcast explores GraphSAGE, graph-native machine learning, and the role of model catalogs in building intelligent applications with Neo4j. It discusses node embeddings, graph-based prediction techniques, and how connected data can enhance machine learning performance. Perfect for data scientists, AI engineers, developers, and technology enthusiasts interested in graph analytics and next-generation machine learning.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72293970</guid><pubDate>Tue, 15 Mar 2022 02:40:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72293970/47_graph_native_learning_introducing_graphsage_and_model_catalogs_in_neo4j_b5arpfip0oe.mp3" length="44918235" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/4851c9de-a9b7-44f4-add6-dfe981479f86/4851c9de-a9b7-44f4-add6-dfe981479f86.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/4851c9de-a9b7-44f4-add6-dfe981479f86/4851c9de-a9b7-44f4-add6-dfe981479f86.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/4851c9de-a9b7-44f4-add6-dfe981479f86/4851c9de-a9b7-44f4-add6-dfe981479f86.vtt" type="text/vtt" language="en"/><itunes:author>HAKKARI GOWENT FM</itunes:author><itunes:subtitle>This podcast explores GraphSAGE, graph-native machine learning, and the role of model catalogs in building intelligent applications with Neo4j. It discusses node embeddings, graph-based prediction techniques, and how connected data can enhance machine...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores GraphSAGE, graph-native machine learning, and the role of model catalogs in building intelligent applications with Neo4j. It discusses node embeddings, graph-based prediction techniques, and how connected data can enhance machine learning performance. Perfect for data scientists, AI engineers, developers, and technology enthusiasts interested in graph analytics and next-generation machine learning.]]></itunes:summary><itunes:duration>2808</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/blue_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item></channel></rss>
