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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>The Modern Muse</title><link>https://www.spreaker.com/podcast/the-modern-muse--7102092</link><description><![CDATA[Explore contemporary art, emerging trends, and the future of creative expression. From galleries and exhibitions to digital innovation, this podcast highlights the evolving landscape of the arts.<br /><br /><br /><br /><br /><br />]]></description><atom:link href="https://www.spreaker.com/show/7102092/episodes/feed" rel="self" type="application/rss+xml"/><language>en</language><category>Arts</category><copyright>Copyright Marthinusbaloyi</copyright><image><url>https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/black_square_mic.jpg</url><title>The Modern Muse</title><link>https://www.spreaker.com/podcast/the-modern-muse--7102092</link></image><lastBuildDate>Wed, 17 Jun 2026 14:48:58 +0000</lastBuildDate><itunes:author>Marthinusbaloyi</itunes:author><itunes:owner><itunes:name>Marthinusbaloyi</itunes:name><itunes:email>feeds@spreaker.com</itunes:email></itunes:owner><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/black_square_mic.jpg"/><itunes:subtitle>Explore contemporary art, emerging trends, and the future of creative expression. From galleries and exhibitions to digital innovation, this podcast highlights the evolving landscape of the arts.</itunes:subtitle><itunes:summary><![CDATA[Explore contemporary art, emerging trends, and the future of creative expression. From galleries and exhibitions to digital innovation, this podcast highlights the evolving landscape of the arts.<br /><br /><br /><br /><br /><br />]]></itunes:summary><itunes:category text="Arts"/><itunes:explicit>false</itunes:explicit><itunes:type>episodic</itunes:type><item><title>Boosting Machine Learning Accuracy with Graph Embeddings</title><link>https://www.spreaker.com/episode/boosting-machine-learning-accuracy-with-graph-embeddings--72563456</link><description><![CDATA[This podcast explores how graph embeddings enhance predictive machine learning models by capturing relationships, context, and hidden patterns within connected data. It discusses graph representation learning, feature enrichment, node embeddings, link prediction, and practical applications that improve model performance across industries. Perfect for data scientists, machine learning engineers, AI researchers, and analytics professionals looking to increase predictive accuracy using graph-powered intelligence.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72563456</guid><pubDate>Fri, 09 Aug 2019 11:20:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72563456/098_rdbms_to_neo4j_real_time_data_sync_with_debezium_and_kafka_nodes2022_nicolas_mervaillie_alf_tybfzh_jrdi.mp3" length="15429983" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/7be42ca8-76f4-436f-831b-aa91ec5f10f9/7be42ca8-76f4-436f-831b-aa91ec5f10f9.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/7be42ca8-76f4-436f-831b-aa91ec5f10f9/7be42ca8-76f4-436f-831b-aa91ec5f10f9.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/7be42ca8-76f4-436f-831b-aa91ec5f10f9/7be42ca8-76f4-436f-831b-aa91ec5f10f9.vtt" type="text/vtt" language="en"/><itunes:author>Marthinusbaloyi</itunes:author><itunes:subtitle>This podcast explores how graph embeddings enhance predictive machine learning models by capturing relationships, context, and hidden patterns within connected data. It discusses graph representation learning, feature enrichment, node embeddings, link...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how graph embeddings enhance predictive machine learning models by capturing relationships, context, and hidden patterns within connected data. It discusses graph representation learning, feature enrichment, node embeddings, link prediction, and practical applications that improve model performance across industries. Perfect for data scientists, machine learning engineers, AI researchers, and analytics professionals looking to increase predictive accuracy using graph-powered intelligence.]]></itunes:summary><itunes:duration>965</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/black_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>The Art of Reinvention</title><link>https://www.spreaker.com/episode/the-art-of-reinvention--72497386</link><description><![CDATA[Creativity thrives on change. This episode explores how creators adapt, evolve, and reinvent themselves while staying true to their unique vision in a rapidly changing world.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72497386</guid><pubDate>Sun, 09 Jun 2019 15:55:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72497386/046_learn_neo4j_in_chinese_with_neo4j_graphacademy_nodes2022_shiny_zhu_z4wqwat6mwi.mp3" length="10694479" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/87d0e74f-41e1-4c8a-8413-338340d34162/87d0e74f-41e1-4c8a-8413-338340d34162.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/87d0e74f-41e1-4c8a-8413-338340d34162/87d0e74f-41e1-4c8a-8413-338340d34162.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/87d0e74f-41e1-4c8a-8413-338340d34162/87d0e74f-41e1-4c8a-8413-338340d34162.vtt" type="text/vtt" language="en"/><itunes:author>Marthinusbaloyi</itunes:author><itunes:subtitle>Creativity thrives on change. This episode explores how creators adapt, evolve, and reinvent themselves while staying true to their unique vision in a rapidly changing world.</itunes:subtitle><itunes:summary><![CDATA[Creativity thrives on change. This episode explores how creators adapt, evolve, and reinvent themselves while staying true to their unique vision in a rapidly changing world.]]></itunes:summary><itunes:duration>669</itunes:duration><itunes:keywords>art</itunes:keywords><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/black_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Finding Inspiration Everywhere</title><link>https://www.spreaker.com/episode/finding-inspiration-everywhere--72497385</link><description><![CDATA[Great ideas often come from the most unexpected places. Join us as we discuss practical ways to cultivate creativity and turn everyday experiences into meaningful artistic expression.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72497385</guid><pubDate>Sun, 10 Feb 2019 13:19:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72497385/045_running_neo4j_in_docker_and_deploying_neo4j_application_in_openshift_nodes2022_payel_bhunia_zevaiaucz60.mp3" length="7099219" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/db9dc616-6654-4119-93c0-f429243e9555/db9dc616-6654-4119-93c0-f429243e9555.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/db9dc616-6654-4119-93c0-f429243e9555/db9dc616-6654-4119-93c0-f429243e9555.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/db9dc616-6654-4119-93c0-f429243e9555/db9dc616-6654-4119-93c0-f429243e9555.vtt" type="text/vtt" language="en"/><itunes:author>Marthinusbaloyi</itunes:author><itunes:subtitle>Great ideas often come from the most unexpected places. Join us as we discuss practical ways to cultivate creativity and turn everyday experiences into meaningful artistic expression.</itunes:subtitle><itunes:summary><![CDATA[Great ideas often come from the most unexpected places. Join us as we discuss practical ways to cultivate creativity and turn everyday experiences into meaningful artistic expression.]]></itunes:summary><itunes:duration>444</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/black_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Turning Technical Vision into Business Value</title><link>https://www.spreaker.com/episode/turning-technical-vision-into-business-value--72563457</link><description><![CDATA[This podcast explores how developers and technology teams can build compelling business cases for graph database projects and connected data initiatives. It discusses identifying business value, measuring ROI, communicating technical benefits to stakeholders, and aligning graph solutions with organizational goals. Perfect for developers, solution architects, project leaders, and technology decision-makers looking to secure support and investment for graph-powered innovations.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72563457</guid><pubDate>Sat, 09 Feb 2019 11:25:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72563457/101_a_developer_s_guide_to_building_a_graph_project_value_case_nodes2022_rik_van_bruggen_uxe1hbjrbe0.mp3" length="18817534" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/61b30097-ecbf-456e-b202-2e210dcb02d0/61b30097-ecbf-456e-b202-2e210dcb02d0.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/61b30097-ecbf-456e-b202-2e210dcb02d0/61b30097-ecbf-456e-b202-2e210dcb02d0.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/61b30097-ecbf-456e-b202-2e210dcb02d0/61b30097-ecbf-456e-b202-2e210dcb02d0.vtt" type="text/vtt" language="en"/><itunes:author>Marthinusbaloyi</itunes:author><itunes:subtitle>This podcast explores how developers and technology teams can build compelling business cases for graph database projects and connected data initiatives. It discusses identifying business value, measuring ROI, communicating technical benefits to...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how developers and technology teams can build compelling business cases for graph database projects and connected data initiatives. It discusses identifying business value, measuring ROI, communicating technical benefits to stakeholders, and aligning graph solutions with organizational goals. Perfect for developers, solution architects, project leaders, and technology decision-makers looking to secure support and investment for graph-powered innovations.]]></itunes:summary><itunes:duration>1177</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/black_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Graph Evolution</title><link>https://www.spreaker.com/episode/graph-evolution--72563454</link><description><![CDATA[This podcast explores modern approaches to managing schema evolution and database refactoring in Neo4j through migration-driven workflows. It discusses version control for graph databases, automated deployments, change management, CI/CD integration, and best practices for maintaining consistency across development and production environments. Perfect for developers, DevOps engineers, database administrators, and architects looking to streamline Neo4j database lifecycle management.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72563454</guid><pubDate>Thu, 08 Feb 2018 11:15:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72563454/099_neo4j_migrations_the_lean_way_of_applying_database_refactorings_to_neo4j_nodes2022_5_j0xivaeom.mp3" length="34891822" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/4184bdbb-e3ae-4452-84ab-6170a935a26f/4184bdbb-e3ae-4452-84ab-6170a935a26f.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/4184bdbb-e3ae-4452-84ab-6170a935a26f/4184bdbb-e3ae-4452-84ab-6170a935a26f.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/4184bdbb-e3ae-4452-84ab-6170a935a26f/4184bdbb-e3ae-4452-84ab-6170a935a26f.vtt" type="text/vtt" language="en"/><itunes:author>Marthinusbaloyi</itunes:author><itunes:subtitle>This podcast explores modern approaches to managing schema evolution and database refactoring in Neo4j through migration-driven workflows. It discusses version control for graph databases, automated deployments, change management, CI/CD integration,...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores modern approaches to managing schema evolution and database refactoring in Neo4j through migration-driven workflows. It discusses version control for graph databases, automated deployments, change management, CI/CD integration, and best practices for maintaining consistency across development and production environments. Perfect for developers, DevOps engineers, database administrators, and architects looking to streamline Neo4j database lifecycle management.]]></itunes:summary><itunes:duration>2181</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/black_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Improving Machine Learning with Graph Embeddings</title><link>https://www.spreaker.com/episode/improving-machine-learning-with-graph-embeddings--72563455</link><description><![CDATA[This podcast explores how graph embeddings enhance machine learning models by capturing relationships and context that traditional tabular data often misses. It discusses representation learning, feature engineering, graph data science techniques, and real-world applications where graph embeddings significantly improve predictive accuracy. Perfect for data scientists, machine learning engineers, AI practitioners, and analytics professionals looking to unlock deeper insights from connected data.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72563455</guid><pubDate>Fri, 14 Jul 2017 12:15:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72563455/100_ml_innovation_more_accuracy_in_predictive_models_thanks_to_graph_embeddings_nodes2022_vyydc3na2te.mp3" length="35673409" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/5d96d57a-de86-44ab-9657-5c174cad92a4/5d96d57a-de86-44ab-9657-5c174cad92a4.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/5d96d57a-de86-44ab-9657-5c174cad92a4/5d96d57a-de86-44ab-9657-5c174cad92a4.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/5d96d57a-de86-44ab-9657-5c174cad92a4/5d96d57a-de86-44ab-9657-5c174cad92a4.vtt" type="text/vtt" language="en"/><itunes:author>Marthinusbaloyi</itunes:author><itunes:subtitle>This podcast explores how graph embeddings enhance machine learning models by capturing relationships and context that traditional tabular data often misses. It discusses representation learning, feature engineering, graph data science techniques, and...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how graph embeddings enhance machine learning models by capturing relationships and context that traditional tabular data often misses. It discusses representation learning, feature engineering, graph data science techniques, and real-world applications where graph embeddings significantly improve predictive accuracy. Perfect for data scientists, machine learning engineers, AI practitioners, and analytics professionals looking to unlock deeper insights from connected data.]]></itunes:summary><itunes:duration>2230</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/black_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item></channel></rss>
