ºÝºÝߣshows by User: caroljmcdonald / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: caroljmcdonald / Tue, 08 Dec 2020 21:22:30 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: caroljmcdonald Introduction to machine learning with GPUs /slideshow/introduction-to-machine-learning-with-gpus/239888412 gpumachinelearningintronvidia-201208212230
Demystifying machine learning and deep learning ]]>
Demystifying machine learning and deep learning ]]> Tue, 08 Dec 2020 21:22:30 GMT /slideshow/introduction-to-machine-learning-with-gpus/239888412 caroljmcdonald@slideshare.net(caroljmcdonald) Introduction to machine learning with GPUs caroljmcdonald Demystifying machine learning and deep learning <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/gpumachinelearningintronvidia-201208212230-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Demystifying machine learning and deep learning
Introduction to machine learning with GPUs from Carol McDonald
]]> 461 0 https://cdn.slidesharecdn.com/ss_thumbnails/gpumachinelearningintronvidia-201208212230-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 Streaming healthcare Data pipeline using Apache APIs: Kafka and Spark with MapR Database /slideshow/streaming-healthcare-data-pipeline-using-apache-apis-kafka-and-spark-with-mapr-database/129883603 streamhealthdata-190130185832
Streaming Data Pipeline to Transform, Store and Explore Healthcare Dataset With Apache Kafka API, Apache Spark, Apache Drill, JSON and MapR-DB]]>
Streaming Data Pipeline to Transform, Store and Explore Healthcare Dataset With Apache Kafka API, Apache Spark, Apache Drill, JSON and MapR-DB]]> Wed, 30 Jan 2019 18:58:32 GMT /slideshow/streaming-healthcare-data-pipeline-using-apache-apis-kafka-and-spark-with-mapr-database/129883603 caroljmcdonald@slideshare.net(caroljmcdonald) Streaming healthcare Data pipeline using Apache APIs: Kafka and Spark with MapR Database caroljmcdonald Streaming Data Pipeline to Transform, Store and Explore Healthcare Dataset With Apache Kafka API, Apache Spark, Apache Drill, JSON and MapR-DB <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/streamhealthdata-190130185832-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Streaming Data Pipeline to Transform, Store and Explore Healthcare Dataset With Apache Kafka API, Apache Spark, Apache Drill, JSON and MapR-DB
Streaming healthcare Data pipeline using Apache APIs: Kafka and Spark with MapR Database from Carol McDonald
]]> 1634 7 https://cdn.slidesharecdn.com/ss_thumbnails/streamhealthdata-190130185832-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 Analyzing Flight Delays with Apache Spark, DataFrames, GraphFrames, and MapR-DB /slideshow/analyzing-flight-delays-with-apache-spark-dataframes-graphframes-and-maprdb/123012777 maprgraphframeswebinar-181114171818
Apache Spark GraphX made it possible to run graph algorithms within Spark, GraphFrames integrates GraphX and DataFrames and makes it possible to perform Graph pattern queries without moving data to a specialized graph database. This presentation will help you get started using Apache Spark GraphFrames Graph Algorithms and Graph Queries with MapR-DB JSON document database. ]]>
Apache Spark GraphX made it possible to run graph algorithms within Spark, GraphFrames integrates GraphX and DataFrames and makes it possible to perform Graph pattern queries without moving data to a specialized graph database. This presentation will help you get started using Apache Spark GraphFrames Graph Algorithms and Graph Queries with MapR-DB JSON document database. ]]> Wed, 14 Nov 2018 17:18:18 GMT /slideshow/analyzing-flight-delays-with-apache-spark-dataframes-graphframes-and-maprdb/123012777 caroljmcdonald@slideshare.net(caroljmcdonald) Analyzing Flight Delays with Apache Spark, DataFrames, GraphFrames, and MapR-DB caroljmcdonald Apache Spark GraphX made it possible to run graph algorithms within Spark, GraphFrames integrates GraphX and DataFrames and makes it possible to perform Graph pattern queries without moving data to a specialized graph database. This presentation will help you get started using Apache Spark GraphFrames Graph Algorithms and Graph Queries with MapR-DB JSON document database. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/maprgraphframeswebinar-181114171818-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Apache Spark GraphX made it possible to run graph algorithms within Spark, GraphFrames integrates GraphX and DataFrames and makes it possible to perform Graph pattern queries without moving data to a specialized graph database. This presentation will help you get started using Apache Spark GraphFrames Graph Algorithms and Graph Queries with MapR-DB JSON document database.
Analyzing Flight Delays with Apache Spark, DataFrames, GraphFrames, and MapR-DB from Carol McDonald
]]> 1010 4 https://cdn.slidesharecdn.com/ss_thumbnails/maprgraphframeswebinar-181114171818-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 Analysis of Popular Uber Locations using Apache APIs: Spark Machine Learning, Structured Streaming, Kafka with MapR-ES and MapR-DB /slideshow/analysis-of-popular-uber-locations-using-apache-apis-spark-machine-learning-structured-streaming-kafka-with-mapres-and-maprdb/121222484 structuredstreamingwebinar-181030180409
Real-Time Analysis of Popular Uber Locations using Apache APIs: Spark Machine Learning, Spark Structured Streaming, Kafka with MapR-ES and MapR-DB ]]>
Real-Time Analysis of Popular Uber Locations using Apache APIs: Spark Machine Learning, Spark Structured Streaming, Kafka with MapR-ES and MapR-DB ]]> Tue, 30 Oct 2018 18:04:09 GMT /slideshow/analysis-of-popular-uber-locations-using-apache-apis-spark-machine-learning-structured-streaming-kafka-with-mapres-and-maprdb/121222484 caroljmcdonald@slideshare.net(caroljmcdonald) Analysis of Popular Uber Locations using Apache APIs: Spark Machine Learning, Structured Streaming, Kafka with MapR-ES and MapR-DB caroljmcdonald Real-Time Analysis of Popular Uber Locations using Apache APIs: Spark Machine Learning, Spark Structured Streaming, Kafka with MapR-ES and MapR-DB <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/structuredstreamingwebinar-181030180409-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Real-Time Analysis of Popular Uber Locations using Apache APIs: Spark Machine Learning, Spark Structured Streaming, Kafka with MapR-ES and MapR-DB
Analysis of Popular Uber Locations using Apache APIs: Spark Machine Learning, Structured Streaming, Kafka with MapR-ES and MapR-DB from Carol McDonald
]]> 929 2 https://cdn.slidesharecdn.com/ss_thumbnails/structuredstreamingwebinar-181030180409-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 Predicting Flight Delays with Spark Machine Learning /slideshow/predicting-flight-delays-with-spark-machine-learning/119631906 flightdelaywebinar-181016182946
Apache Spark's MLlib makes machine learning scalable and easier with ML pipelines built on top of DataFrames. In this webinar, we will go over an example from the ebook Getting Started with Apache Spark 2.x.: predicting flight delays using Apache Spark machine learning. ]]>
Apache Spark's MLlib makes machine learning scalable and easier with ML pipelines built on top of DataFrames. In this webinar, we will go over an example from the ebook Getting Started with Apache Spark 2.x.: predicting flight delays using Apache Spark machine learning. ]]> Tue, 16 Oct 2018 18:29:46 GMT /slideshow/predicting-flight-delays-with-spark-machine-learning/119631906 caroljmcdonald@slideshare.net(caroljmcdonald) Predicting Flight Delays with Spark Machine Learning caroljmcdonald Apache Spark's MLlib makes machine learning scalable and easier with ML pipelines built on top of DataFrames. In this webinar, we will go over an example from the ebook Getting Started with Apache Spark 2.x.: predicting flight delays using Apache Spark machine learning. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/flightdelaywebinar-181016182946-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Apache Spark&#39;s MLlib makes machine learning scalable and easier with ML pipelines built on top of DataFrames. In this webinar, we will go over an example from the ebook Getting Started with Apache Spark 2.x.: predicting flight delays using Apache Spark machine learning.
Predicting Flight Delays with Spark Machine Learning from Carol McDonald
]]> 2379 2 https://cdn.slidesharecdn.com/ss_thumbnails/flightdelaywebinar-181016182946-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 Structured Streaming Data Pipeline Using Kafka, Spark, and MapR-DB /slideshow/structured-streaming-data-pipeline-using-kafka-spark-and-maprdb/103375554 etlstructuedstreaming-180628032852
Structured Streaming Data Pipeline Using Kafka, Spark, and MapR-DB]]>
Structured Streaming Data Pipeline Using Kafka, Spark, and MapR-DB]]> Thu, 28 Jun 2018 03:28:52 GMT /slideshow/structured-streaming-data-pipeline-using-kafka-spark-and-maprdb/103375554 caroljmcdonald@slideshare.net(caroljmcdonald) Structured Streaming Data Pipeline Using Kafka, Spark, and MapR-DB caroljmcdonald Structured Streaming Data Pipeline Using Kafka, Spark, and MapR-DB <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/etlstructuedstreaming-180628032852-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Structured Streaming Data Pipeline Using Kafka, Spark, and MapR-DB
Structured Streaming Data Pipeline Using Kafka, Spark, and MapR-DB from Carol McDonald
]]> 1286 5 https://cdn.slidesharecdn.com/ss_thumbnails/etlstructuedstreaming-180628032852-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 Streaming Machine learning Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase /slideshow/streaming-machine-learning-distributed-pipeline-for-realtime-uber-data-using-apache-apis-kafka-spark-hbase/94135094 machinelearningiotrealtimepipeline-180417193640
Streaming Machine learning Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase ]]>
Streaming Machine learning Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase ]]> Tue, 17 Apr 2018 19:36:40 GMT /slideshow/streaming-machine-learning-distributed-pipeline-for-realtime-uber-data-using-apache-apis-kafka-spark-hbase/94135094 caroljmcdonald@slideshare.net(caroljmcdonald) Streaming Machine learning Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase caroljmcdonald Streaming Machine learning Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/machinelearningiotrealtimepipeline-180417193640-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Streaming Machine learning Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase
Streaming Machine learning Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase from Carol McDonald
]]> 1997 12 https://cdn.slidesharecdn.com/ss_thumbnails/machinelearningiotrealtimepipeline-180417193640-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 Applying Machine Learning to IOT: End to End Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase /slideshow/applying-machine-learning-to-iot-end-to-end-distributed-pipeline-for-realtime-uber-data-using-apache-apis-kafka-spark-hbase/88731096 atlantalong-180223154316
Using Spark Streaming , machine learning , kafka, hbase in a fast data pipeline]]>
Using Spark Streaming , machine learning , kafka, hbase in a fast data pipeline]]> Fri, 23 Feb 2018 15:43:15 GMT /slideshow/applying-machine-learning-to-iot-end-to-end-distributed-pipeline-for-realtime-uber-data-using-apache-apis-kafka-spark-hbase/88731096 caroljmcdonald@slideshare.net(caroljmcdonald) Applying Machine Learning to IOT: End to End Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase caroljmcdonald Using Spark Streaming , machine learning , kafka, hbase in a fast data pipeline <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/atlantalong-180223154316-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Using Spark Streaming , machine learning , kafka, hbase in a fast data pipeline
Applying Machine Learning to IOT: End to End Distributed Pipeline for Real-Time Uber Data Using Apache APIs: Kafka, Spark, HBase from Carol McDonald
]]> 1086 11 https://cdn.slidesharecdn.com/ss_thumbnails/atlantalong-180223154316-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 Applying Machine Learning to IOT: End to End Distributed Pipeline for Real- Time Uber Data Using Apache APIs: Kafka, Spark, HBase /caroljmcdonald/applying-machine-learning-to-iot-end-to-end-distributed-pipeline-for-real-time-uber-data-using-apache-apis-kafka-spark-hbase iotmachinelearningendtoendpipeineapacheapikafkasparkboston-171103023623
Applying Machine Learning to IOT: End to End Distributed Pipeline for Real- Time Uber Data Using Apache APIs: Kafka, Spark, HBase]]>
Applying Machine Learning to IOT: End to End Distributed Pipeline for Real- Time Uber Data Using Apache APIs: Kafka, Spark, HBase]]> Fri, 03 Nov 2017 02:36:23 GMT /caroljmcdonald/applying-machine-learning-to-iot-end-to-end-distributed-pipeline-for-real-time-uber-data-using-apache-apis-kafka-spark-hbase caroljmcdonald@slideshare.net(caroljmcdonald) Applying Machine Learning to IOT: End to End Distributed Pipeline for Real- Time Uber Data Using Apache APIs: Kafka, Spark, HBase caroljmcdonald Applying Machine Learning to IOT: End to End Distributed Pipeline for Real- Time Uber Data Using Apache APIs: Kafka, Spark, HBase <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iotmachinelearningendtoendpipeineapacheapikafkasparkboston-171103023623-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Applying Machine Learning to IOT: End to End Distributed Pipeline for Real- Time Uber Data Using Apache APIs: Kafka, Spark, HBase
Applying Machine Learning to IOT: End to End Distributed Pipeline for Real- Time Uber Data Using Apache APIs: Kafka, Spark, HBase from Carol McDonald
]]> 2803 7 https://cdn.slidesharecdn.com/ss_thumbnails/iotmachinelearningendtoendpipeineapacheapikafkasparkboston-171103023623-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 How Big Data is Reducing Costs and Improving Outcomes in Health Care /slideshow/how-big-data-is-reducing-costs-and-improving-outcomes-in-health-care/79227734 bigdatahealthcarenashville4-170828203015
There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics. Join this talk to hear how MapR customers are using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer. We will cover big data healthcare trends and production use cases that demonstrate how to deliver data-driven healthcare applications]]>
There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics. Join this talk to hear how MapR customers are using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer. We will cover big data healthcare trends and production use cases that demonstrate how to deliver data-driven healthcare applications]]> Mon, 28 Aug 2017 20:30:14 GMT /slideshow/how-big-data-is-reducing-costs-and-improving-outcomes-in-health-care/79227734 caroljmcdonald@slideshare.net(caroljmcdonald) How Big Data is Reducing Costs and Improving Outcomes in Health Care caroljmcdonald There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics. Join this talk to hear how MapR customers are using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer. We will cover big data healthcare trends and production use cases that demonstrate how to deliver data-driven healthcare applications <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/bigdatahealthcarenashville4-170828203015-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics. Join this talk to hear how MapR customers are using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer. We will cover big data healthcare trends and production use cases that demonstrate how to deliver data-driven healthcare applications
How Big Data is Reducing Costs and Improving Outcomes in Health Care from Carol McDonald
]]> 1044 7 https://cdn.slidesharecdn.com/ss_thumbnails/bigdatahealthcarenashville4-170828203015-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Demystifying AI, Machine Learning and Deep Learning /slideshow/demystifying-ai-machine-learning-and-deep-learning/79227583 dymystifyingmlnashville-170828202329
Deep learning, machine learning, artificial intelligence - all buzzwords and representative of the future of analytics. In this talk we will explain what is machine learning and deep learning at a high level with some real world examples. The goal of this is not to turn you into a data scientist, but to give you a better understanding of what you can do with machine learning. Machine learning is becoming more accessible to developers, and Data scientists work with domain experts, architects, developers and data engineers, so it is important for everyone to have a better understanding of the possibilities. Every piece of information that your business generates has potential to add value. This and future posts are meant to provoke a review of your own data to identify new opportunities.]]>
Deep learning, machine learning, artificial intelligence - all buzzwords and representative of the future of analytics. In this talk we will explain what is machine learning and deep learning at a high level with some real world examples. The goal of this is not to turn you into a data scientist, but to give you a better understanding of what you can do with machine learning. Machine learning is becoming more accessible to developers, and Data scientists work with domain experts, architects, developers and data engineers, so it is important for everyone to have a better understanding of the possibilities. Every piece of information that your business generates has potential to add value. This and future posts are meant to provoke a review of your own data to identify new opportunities.]]> Mon, 28 Aug 2017 20:23:29 GMT /slideshow/demystifying-ai-machine-learning-and-deep-learning/79227583 caroljmcdonald@slideshare.net(caroljmcdonald) Demystifying AI, Machine Learning and Deep Learning caroljmcdonald Deep learning, machine learning, artificial intelligence - all buzzwords and representative of the future of analytics. In this talk we will explain what is machine learning and deep learning at a high level with some real world examples. The goal of this is not to turn you into a data scientist, but to give you a better understanding of what you can do with machine learning. Machine learning is becoming more accessible to developers, and Data scientists work with domain experts, architects, developers and data engineers, so it is important for everyone to have a better understanding of the possibilities. Every piece of information that your business generates has potential to add value. This and future posts are meant to provoke a review of your own data to identify new opportunities. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dymystifyingmlnashville-170828202329-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Deep learning, machine learning, artificial intelligence - all buzzwords and representative of the future of analytics. In this talk we will explain what is machine learning and deep learning at a high level with some real world examples. The goal of this is not to turn you into a data scientist, but to give you a better understanding of what you can do with machine learning. Machine learning is becoming more accessible to developers, and Data scientists work with domain experts, architects, developers and data engineers, so it is important for everyone to have a better understanding of the possibilities. Every piece of information that your business generates has potential to add value. This and future posts are meant to provoke a review of your own data to identify new opportunities.
Demystifying AI, Machine Learning and Deep Learning from Carol McDonald
]]> 895 8 https://cdn.slidesharecdn.com/ss_thumbnails/dymystifyingmlnashville-170828202329-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Spark graphx /slideshow/spark-graphx/77966657 sparkgraphx-170717181508
Introduction to Apache Spark GraphX ]]>
Introduction to Apache Spark GraphX ]]> Mon, 17 Jul 2017 18:15:08 GMT /slideshow/spark-graphx/77966657 caroljmcdonald@slideshare.net(caroljmcdonald) Spark graphx caroljmcdonald Introduction to Apache Spark GraphX <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sparkgraphx-170717181508-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Introduction to Apache Spark GraphX
Spark graphx from Carol McDonald
]]> 1730 4 https://cdn.slidesharecdn.com/ss_thumbnails/sparkgraphx-170717181508-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Applying Machine learning to IOT: End to End Distributed Distributed Pipeline for Realtime Uber Montoring Dashboard using Apache APIs: Kafka Spark HBase /slideshow/applying-machine-learning-to-iot-end-to-end-distributed-distributed-pipeline-for-realtime-uber-montoring-dashboard-using-apache-apis-kafka-spark-hbase/77839874 realtimeuber2-170713155223
This discusses the architecture of an end-to-end application that combines streaming data with machine learning to do real-time analysis and visualization of where and when Uber cars are clustered, so as to analyze and visualize the most popular Uber locations.]]>
This discusses the architecture of an end-to-end application that combines streaming data with machine learning to do real-time analysis and visualization of where and when Uber cars are clustered, so as to analyze and visualize the most popular Uber locations.]]> Thu, 13 Jul 2017 15:52:23 GMT /slideshow/applying-machine-learning-to-iot-end-to-end-distributed-distributed-pipeline-for-realtime-uber-montoring-dashboard-using-apache-apis-kafka-spark-hbase/77839874 caroljmcdonald@slideshare.net(caroljmcdonald) Applying Machine learning to IOT: End to End Distributed Distributed Pipeline for Realtime Uber Montoring Dashboard using Apache APIs: Kafka Spark HBase caroljmcdonald This discusses the architecture of an end-to-end application that combines streaming data with machine learning to do real-time analysis and visualization of where and when Uber cars are clustered, so as to analyze and visualize the most popular Uber locations. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/realtimeuber2-170713155223-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This discusses the architecture of an end-to-end application that combines streaming data with machine learning to do real-time analysis and visualization of where and when Uber cars are clustered, so as to analyze and visualize the most popular Uber locations.
Applying Machine learning to IOT: End to End Distributed Distributed Pipeline for Realtime Uber Montoring Dashboard using Apache APIs: Kafka Spark HBase from Carol McDonald
]]> 1003 7 https://cdn.slidesharecdn.com/ss_thumbnails/realtimeuber2-170713155223-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Streaming patterns revolutionary architectures /slideshow/streaming-patterns-revolutionary-architectures-77182920/77182920 streamingpatternsrevolutionaryarchitecturesupload-170622171531
The Stream as the system of Record , CQRS , other streaming patterns and examples]]>
The Stream as the system of Record , CQRS , other streaming patterns and examples]]> Thu, 22 Jun 2017 17:15:31 GMT /slideshow/streaming-patterns-revolutionary-architectures-77182920/77182920 caroljmcdonald@slideshare.net(caroljmcdonald) Streaming patterns revolutionary architectures caroljmcdonald The Stream as the system of Record , CQRS , other streaming patterns and examples <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/streamingpatternsrevolutionaryarchitecturesupload-170622171531-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The Stream as the system of Record , CQRS , other streaming patterns and examples
Streaming patterns revolutionary architectures from Carol McDonald
]]> 514 5 https://cdn.slidesharecdn.com/ss_thumbnails/streamingpatternsrevolutionaryarchitecturesupload-170622171531-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Spark machine learning predicting customer churn /caroljmcdonald/spark-machine-learning-predicting-customer-churn sparkmachinelearningchurn7-170616145947
Using Spark Machine learning to predict customer churn]]>
Using Spark Machine learning to predict customer churn]]> Fri, 16 Jun 2017 14:59:47 GMT /caroljmcdonald/spark-machine-learning-predicting-customer-churn caroljmcdonald@slideshare.net(caroljmcdonald) Spark machine learning predicting customer churn caroljmcdonald Using Spark Machine learning to predict customer churn <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sparkmachinelearningchurn7-170616145947-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Using Spark Machine learning to predict customer churn
Spark machine learning predicting customer churn from Carol McDonald
]]> 1316 6 https://cdn.slidesharecdn.com/ss_thumbnails/sparkmachinelearningchurn7-170616145947-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 Fast Cars, Big Data How Streaming can help Formula 1 /slideshow/fast-cars-big-data-how-streaming-can-help-formula-1-76100757/76100757 fastcarbigdatacodemotioncarol3-170518170145
Fast Cars, Big Data How Streaming can help Formula 1]]>
Fast Cars, Big Data How Streaming can help Formula 1]]> Thu, 18 May 2017 17:01:45 GMT /slideshow/fast-cars-big-data-how-streaming-can-help-formula-1-76100757/76100757 caroljmcdonald@slideshare.net(caroljmcdonald) Fast Cars, Big Data How Streaming can help Formula 1 caroljmcdonald Fast Cars, Big Data How Streaming can help Formula 1 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/fastcarbigdatacodemotioncarol3-170518170145-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Fast Cars, Big Data How Streaming can help Formula 1
Fast Cars, Big Data How Streaming can help Formula 1 from Carol McDonald
]]> 952 5 https://cdn.slidesharecdn.com/ss_thumbnails/fastcarbigdatacodemotioncarol3-170518170145-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Applying Machine Learning to Live Patient Data /slideshow/applying-machine-learning-to-live-patient-data/73185134 ekgmarch15final-170315184804
Applying Machine Learning to Live Patient Data using Apache Spark ]]>
Applying Machine Learning to Live Patient Data using Apache Spark ]]> Wed, 15 Mar 2017 18:48:04 GMT /slideshow/applying-machine-learning-to-live-patient-data/73185134 caroljmcdonald@slideshare.net(caroljmcdonald) Applying Machine Learning to Live Patient Data caroljmcdonald Applying Machine Learning to Live Patient Data using Apache Spark <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ekgmarch15final-170315184804-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Applying Machine Learning to Live Patient Data using Apache Spark
Applying Machine Learning to Live Patient Data from Carol McDonald
]]> 1811 5 https://cdn.slidesharecdn.com/ss_thumbnails/ekgmarch15final-170315184804-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Streaming Patterns Revolutionary Architectures with the Kafka API /slideshow/streaming-patterns-revolutionary-architectures-with-the-kafka-api/65138465 streamspatterns-160818185723
Building a robust, responsive, secure data service for healthcare is tricky. For starters, healthcare data lends itself to multiple models: • Document representation for patient profile view or update • Graph representation to query relationships between patients, providers, and medications • Search representation for advanced lookups Keeping these different systems up to date requires an architecture that can synchronize them in real time as data is updated. Furthermore, meeting audit requirements in Healthcare requires the ability to apply granular cross-datacenter replication policies to data and be able to provide detailed lineage information for each record. This post will describe how stream-first architectures can solve these challenges, and look at how this has been implemented at a Health Information Network provider. This talk will go over the Kafka API with these design patterns: • Turning the database upside down • Event Sourcing , Command Query Responsibity Separation , Polyglot Persistence • Kappa Architecture ]]>
Building a robust, responsive, secure data service for healthcare is tricky. For starters, healthcare data lends itself to multiple models: • Document representation for patient profile view or update • Graph representation to query relationships between patients, providers, and medications • Search representation for advanced lookups Keeping these different systems up to date requires an architecture that can synchronize them in real time as data is updated. Furthermore, meeting audit requirements in Healthcare requires the ability to apply granular cross-datacenter replication policies to data and be able to provide detailed lineage information for each record. This post will describe how stream-first architectures can solve these challenges, and look at how this has been implemented at a Health Information Network provider. This talk will go over the Kafka API with these design patterns: • Turning the database upside down • Event Sourcing , Command Query Responsibity Separation , Polyglot Persistence • Kappa Architecture ]]> Thu, 18 Aug 2016 18:57:23 GMT /slideshow/streaming-patterns-revolutionary-architectures-with-the-kafka-api/65138465 caroljmcdonald@slideshare.net(caroljmcdonald) Streaming Patterns Revolutionary Architectures with the Kafka API caroljmcdonald Building a robust, responsive, secure data service for healthcare is tricky. For starters, healthcare data lends itself to multiple models: • Document representation for patient profile view or update • Graph representation to query relationships between patients, providers, and medications • Search representation for advanced lookups Keeping these different systems up to date requires an architecture that can synchronize them in real time as data is updated. Furthermore, meeting audit requirements in Healthcare requires the ability to apply granular cross-datacenter replication policies to data and be able to provide detailed lineage information for each record. This post will describe how stream-first architectures can solve these challenges, and look at how this has been implemented at a Health Information Network provider. This talk will go over the Kafka API with these design patterns: • Turning the database upside down • Event Sourcing , Command Query Responsibity Separation , Polyglot Persistence • Kappa Architecture <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/streamspatterns-160818185723-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Building a robust, responsive, secure data service for healthcare is tricky. For starters, healthcare data lends itself to multiple models: • Document representation for patient profile view or update • Graph representation to query relationships between patients, providers, and medications • Search representation for advanced lookups Keeping these different systems up to date requires an architecture that can synchronize them in real time as data is updated. Furthermore, meeting audit requirements in Healthcare requires the ability to apply granular cross-datacenter replication policies to data and be able to provide detailed lineage information for each record. This post will describe how stream-first architectures can solve these challenges, and look at how this has been implemented at a Health Information Network provider. This talk will go over the Kafka API with these design patterns: • Turning the database upside down • Event Sourcing , Command Query Responsibity Separation , Polyglot Persistence • Kappa Architecture
Streaming Patterns Revolutionary Architectures with the Kafka API from Carol McDonald
]]> 1056 3 https://cdn.slidesharecdn.com/ss_thumbnails/streamspatterns-160818185723-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Apache Spark Machine Learning Decision Trees /slideshow/apache-spark-machine-learning-decision-trees/63652702 freecodefridaysparkmllib3-160701180327
Predict Flight Delays with Apache Spark's Machine Learning Decision Tree algorithm]]>
Predict Flight Delays with Apache Spark's Machine Learning Decision Tree algorithm]]> Fri, 01 Jul 2016 18:03:26 GMT /slideshow/apache-spark-machine-learning-decision-trees/63652702 caroljmcdonald@slideshare.net(caroljmcdonald) Apache Spark Machine Learning Decision Trees caroljmcdonald Predict Flight Delays with Apache Spark's Machine Learning Decision Tree algorithm <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/freecodefridaysparkmllib3-160701180327-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Predict Flight Delays with Apache Spark&#39;s Machine Learning Decision Tree algorithm
Apache Spark Machine Learning Decision Trees from Carol McDonald
]]> 3084 6 https://cdn.slidesharecdn.com/ss_thumbnails/freecodefridaysparkmllib3-160701180327-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Advanced Threat Detection on Streaming Data /slideshow/advanced-threat-detection-on-streaming-data/61515024 threatdetectiononstreamingdatacm1-160429191432
Advanced Threat Detection on Streaming Data using Kafka , Storm and HBase]]>
Advanced Threat Detection on Streaming Data using Kafka , Storm and HBase]]> Fri, 29 Apr 2016 19:14:32 GMT /slideshow/advanced-threat-detection-on-streaming-data/61515024 caroljmcdonald@slideshare.net(caroljmcdonald) Advanced Threat Detection on Streaming Data caroljmcdonald Advanced Threat Detection on Streaming Data using Kafka , Storm and HBase <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/threatdetectiononstreamingdatacm1-160429191432-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Advanced Threat Detection on Streaming Data using Kafka , Storm and HBase
Advanced Threat Detection on Streaming Data from Carol McDonald
]]> 850 6 https://cdn.slidesharecdn.com/ss_thumbnails/threatdetectiononstreamingdatacm1-160429191432-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-caroljmcdonald-48x48.jpg?cb=1687457239 Carol is PMM at NVIDIA. She developed applications in banking, health insurance, and telecom. She traveled worldwide speaking. https://cdn.slidesharecdn.com/ss_thumbnails/gpumachinelearningintronvidia-201208212230-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/introduction-to-machine-learning-with-gpus/239888412 Introduction to machin... https://cdn.slidesharecdn.com/ss_thumbnails/streamhealthdata-190130185832-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/streaming-healthcare-data-pipeline-using-apache-apis-kafka-and-spark-with-mapr-database/129883603 Streaming healthcare D... https://cdn.slidesharecdn.com/ss_thumbnails/maprgraphframeswebinar-181114171818-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/analyzing-flight-delays-with-apache-spark-dataframes-graphframes-and-maprdb/123012777 Analyzing Flight Delay...