ºÝºÝߣshows by User: CCR_Inc / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: CCR_Inc / Mon, 16 Apr 2018 16:04:32 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: CCR_Inc Training Drone Image Models with Grand Theft Auto /slideshow/training-drone-image-models-with-grand-theft-auto/93986844 trainingimagemodelswithgtamonicarajendiranccri-180416160432
CCRi Data Scientist Monica Rajendiran's presentation from Charlottesville's 2018 #tomtomfest Machine Learning conference.]]>
CCRi Data Scientist Monica Rajendiran's presentation from Charlottesville's 2018 #tomtomfest Machine Learning conference.]]> Mon, 16 Apr 2018 16:04:32 GMT /slideshow/training-drone-image-models-with-grand-theft-auto/93986844 CCR_Inc@slideshare.net(CCR_Inc) Training Drone Image Models with Grand Theft Auto CCR_Inc CCRi Data Scientist Monica Rajendiran's presentation from Charlottesville's 2018 #tomtomfest Machine Learning conference. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/trainingimagemodelswithgtamonicarajendiranccri-180416160432-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> CCRi Data Scientist Monica Rajendiran&#39;s presentation from Charlottesville&#39;s 2018 #tomtomfest Machine Learning conference.
Training Drone Image Models with Grand Theft Auto from Commonwealth Computer Research, Inc.
]]> 2684 8 https://cdn.slidesharecdn.com/ss_thumbnails/trainingimagemodelswithgtamonicarajendiranccri-180416160432-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 GeoMesa on Spark SQL: Extracting Location Intelligence from Data /CCR_Inc/geomesa-on-spark-sql-extracting-location-intelligence-from-data ss2017geomesaonsparksql-170608140558
GeoMesa is an open-source toolkit for processing and analyzing spatio-temporal data, such as IoT and sensor-produced observations, at scale. It provides a consistent API for querying and analyzing data on top of distributed databases (e.g. HBase, Accumulo, Bigtable, Cassandra) and messaging networks (e.g. Kafka) to handle batch analysis of historical archives of data and low-latency processing of data in-stream. GeoMesa has deep integration with Spark SQL. It has added spatial types (e.g. Point, LineString, Polygons), spatial predicates (st_contains, st_intersects, etc.), and geometry processing functions (e.g. st_buffer, st_convexHull, etc.) to Spark SQL. It also optimizes the processing of these extensions by integrating with the Catalyst SQL optimizer to intercept SQL statements with spatial predicates and provision RDDs based on the underlying spatial index. This session demonstrates the implementation of the GeoMesa Spark SQL integration, illustrate its application in production systems and demonstrate spatial aggregations and analytics using map-based visualizations. ]]>
GeoMesa is an open-source toolkit for processing and analyzing spatio-temporal data, such as IoT and sensor-produced observations, at scale. It provides a consistent API for querying and analyzing data on top of distributed databases (e.g. HBase, Accumulo, Bigtable, Cassandra) and messaging networks (e.g. Kafka) to handle batch analysis of historical archives of data and low-latency processing of data in-stream. GeoMesa has deep integration with Spark SQL. It has added spatial types (e.g. Point, LineString, Polygons), spatial predicates (st_contains, st_intersects, etc.), and geometry processing functions (e.g. st_buffer, st_convexHull, etc.) to Spark SQL. It also optimizes the processing of these extensions by integrating with the Catalyst SQL optimizer to intercept SQL statements with spatial predicates and provision RDDs based on the underlying spatial index. This session demonstrates the implementation of the GeoMesa Spark SQL integration, illustrate its application in production systems and demonstrate spatial aggregations and analytics using map-based visualizations. ]]> Thu, 08 Jun 2017 14:05:57 GMT /CCR_Inc/geomesa-on-spark-sql-extracting-location-intelligence-from-data CCR_Inc@slideshare.net(CCR_Inc) GeoMesa on Spark SQL: Extracting Location Intelligence from Data CCR_Inc GeoMesa is an open-source toolkit for processing and analyzing spatio-temporal data, such as IoT and sensor-produced observations, at scale. It provides a consistent API for querying and analyzing data on top of distributed databases (e.g. HBase, Accumulo, Bigtable, Cassandra) and messaging networks (e.g. Kafka) to handle batch analysis of historical archives of data and low-latency processing of data in-stream. GeoMesa has deep integration with Spark SQL. It has added spatial types (e.g. Point, LineString, Polygons), spatial predicates (st_contains, st_intersects, etc.), and geometry processing functions (e.g. st_buffer, st_convexHull, etc.) to Spark SQL. It also optimizes the processing of these extensions by integrating with the Catalyst SQL optimizer to intercept SQL statements with spatial predicates and provision RDDs based on the underlying spatial index. This session demonstrates the implementation of the GeoMesa Spark SQL integration, illustrate its application in production systems and demonstrate spatial aggregations and analytics using map-based visualizations. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ss2017geomesaonsparksql-170608140558-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> GeoMesa is an open-source toolkit for processing and analyzing spatio-temporal data, such as IoT and sensor-produced observations, at scale. It provides a consistent API for querying and analyzing data on top of distributed databases (e.g. HBase, Accumulo, Bigtable, Cassandra) and messaging networks (e.g. Kafka) to handle batch analysis of historical archives of data and low-latency processing of data in-stream. GeoMesa has deep integration with Spark SQL. It has added spatial types (e.g. Point, LineString, Polygons), spatial predicates (st_contains, st_intersects, etc.), and geometry processing functions (e.g. st_buffer, st_convexHull, etc.) to Spark SQL. It also optimizes the processing of these extensions by integrating with the Catalyst SQL optimizer to intercept SQL statements with spatial predicates and provision RDDs based on the underlying spatial index. This session demonstrates the implementation of the GeoMesa Spark SQL integration, illustrate its application in production systems and demonstrate spatial aggregations and analytics using map-based visualizations.
GeoMesa on Spark SQL: Extracting Location Intelligence from Data from Commonwealth Computer Research, Inc.
]]> 1868 4 https://cdn.slidesharecdn.com/ss_thumbnails/ss2017geomesaonsparksql-170608140558-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Learn about Your Location (Using ALL Your Data) /slideshow/learn-about-your-location-using-all-your-data-75018525/75018525 tomtom2017-170414140520
Taryn Price and Courtney Shindeldecker's keynote presentation in the Machine Learning presentatation at the Charlottesville's 2017 Tom Tom Fest.]]>
Taryn Price and Courtney Shindeldecker's keynote presentation in the Machine Learning presentatation at the Charlottesville's 2017 Tom Tom Fest.]]> Fri, 14 Apr 2017 14:05:20 GMT /slideshow/learn-about-your-location-using-all-your-data-75018525/75018525 CCR_Inc@slideshare.net(CCR_Inc) Learn about Your Location (Using ALL Your Data) CCR_Inc Taryn Price and Courtney Shindeldecker's keynote presentation in the Machine Learning presentatation at the Charlottesville's 2017 Tom Tom Fest. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/tomtom2017-170414140520-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Taryn Price and Courtney Shindeldecker&#39;s keynote presentation in the Machine Learning presentatation at the Charlottesville&#39;s 2017 Tom Tom Fest.
Learn about Your Location (Using ALL Your Data) from Commonwealth Computer Research, Inc.
]]> 704 7 https://cdn.slidesharecdn.com/ss_thumbnails/tomtom2017-170414140520-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-CCR_Inc-48x48.jpg?cb=1595015269 CCRi’s vision is to make sense of the world by fusing data from multiple sources, and our mission is to design full-stack, scalable analytics for government, military, marketing and healthcare sectors and implementing those solutions with effective and reliable software. www.ccri.com https://cdn.slidesharecdn.com/ss_thumbnails/trainingimagemodelswithgtamonicarajendiranccri-180416160432-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/training-drone-image-models-with-grand-theft-auto/93986844 Training Drone Image M... https://cdn.slidesharecdn.com/ss_thumbnails/ss2017geomesaonsparksql-170608140558-thumbnail.jpg?width=320&height=320&fit=bounds CCR_Inc/geomesa-on-spark-sql-extracting-location-intelligence-from-data GeoMesa on Spark SQL: ... https://cdn.slidesharecdn.com/ss_thumbnails/tomtom2017-170414140520-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/learn-about-your-location-using-all-your-data-75018525/75018525 Learn about Your Locat...