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School Values Assembly
Perseverance values assembly march
Perseverance values assembly march
tinagage
for unst 254g taught by lea millay. these are the video links for grave of the fireflies.
Sinq video links
Sinq video links
mah8
PUNTUALIDAD, RESPETO Y SOLIDARIDAD
Los valores
Los valores
Lorenamey
es un video tuutorial
Curso de costos y presupuestos
Curso de costos y presupuestos
米 里维拉米
test link of video
Enstn2
Enstn2
msteven1
Spermatopsida
Spermatopsida
miriamyalba
music video idea 1
idea one for music video
idea one for music video
rosie hill
CHOSEN BRAND-LAYS COMPETITOR BRAND-BING0!
Promotions strategy of lays-Sonika Angilin_PGP30174
Promotions strategy of lays-Sonika Angilin_PGP30174
Sameer Mathur
Recommandé
School Values Assembly
Perseverance values assembly march
Perseverance values assembly march
tinagage
for unst 254g taught by lea millay. these are the video links for grave of the fireflies.
Sinq video links
Sinq video links
mah8
PUNTUALIDAD, RESPETO Y SOLIDARIDAD
Los valores
Los valores
Lorenamey
es un video tuutorial
Curso de costos y presupuestos
Curso de costos y presupuestos
米 里维拉米
test link of video
Enstn2
Enstn2
msteven1
Spermatopsida
Spermatopsida
miriamyalba
music video idea 1
idea one for music video
idea one for music video
rosie hill
CHOSEN BRAND-LAYS COMPETITOR BRAND-BING0!
Promotions strategy of lays-Sonika Angilin_PGP30174
Promotions strategy of lays-Sonika Angilin_PGP30174
Sameer Mathur
Presented at the RV College of Engineering Multidisciplinary Trends in Information Technology, July 21 - 25, 2020.
Natural Language to SQL Query conversion using Machine Learning Techniques on...
Natural Language to SQL Query conversion using Machine Learning Techniques on...
HPCC Systems
Presented at the IEEE-RVCE Computer Society Webinar Series
Improving Efficiency of Machine Learning Algorithms using HPCC Systems
Improving Efficiency of Machine Learning Algorithms using HPCC Systems
HPCC Systems
Xian Yang's presentation to ODSC Europe 2019. Yang is a research fellow in the Data Science Institute at Imperial College London.
Towards Trustable AI for Complex Systems
Towards Trustable AI for Complex Systems
HPCC Systems
Closing / Adjourn
Closing / Adjourn
Closing / Adjourn
HPCC Systems
The reveal of how HPCC Systems is improving and expanding around the world for building a global community.
Community Website: Virtual Ribbon Cutting
Community Website: Virtual Ribbon Cutting
HPCC Systems
Come hear a brief overview on the direction the HPCC Systems platform is heading, and get a glimpse into some of the likely highlights included in the next minor and major versions.
Path to 8.0
Path to 8.0
HPCC Systems
This talk will explain the reasoning behind the release cycle changes, and how overcoming the challenges faced in the previous practice of automated testing has introduced new benefits and wider acceptance from the wider community.
Release Cycle Changes
Release Cycle Changes
HPCC Systems
An introductory look at the ECL H3 Plugin (available since v7.2.0) - a journey from lat/long to ROXIE Service driven visualizations
Geohashing with Uber’s H3 Geospatial Index
Geohashing with Uber’s H3 Geospatial Index
HPCC Systems
This presentation will provide an overview of the latest advancements in Machine Learning modules over the past year, including Clustering, Natural Language Processing, Deep Learning, and the Expanded Model Evaluation Metrics. Clustering Methods of the HPCC Systems Machine Learning Library The clustering method is an important part of unsupervised learning. To gain the unsupervised learning capability, two widely applied clustering methods, KMeans and DBSCAN are adopted to the current Machine Learning library. This presentation will introduce the newly developed clustering algorithms and the evaluation methods.
Advancements in HPCC Systems Machine Learning
Advancements in HPCC Systems Machine Learning
HPCC Systems
Learn how to package the HPCC Systems Platform in a Docker container and deploy it locally, and build an HPCC Systems Platform AMI followed by an AWS deployment.
Docker Support
Docker Support
HPCC Systems
The training process for modern deep neural networks requires big data and large computational power. Though HPCC Systems excels at both of these, HPCC Systems is limited to utilizing the CPU only. It has been shown that GPU acceleration vastly improves Deep Learning training time. In this talk, Robert will explain how HPCC Systems became the first GPU accelerated library while also greatly expanding its deep neural network capabilities.
Expanding HPCC Systems Deep Neural Network Capabilities
Expanding HPCC Systems Deep Neural Network Capabilities
HPCC Systems
HPCC Systems offers parallelization by assuming data-independent tasks. For operations having complex predicates, such as the set similarity join (SSJ) predicates, this assumption might create a tradeoff. On the one hand, one may choose a data replication strategy with large intermediate data groups assuring that all intermediate results fit into main memory. However, this can lead to an underutilization of today's massively parallel CPUs. On the other hand, you may choose a higher degree of replication for better CPU utilization. Such a choice may lead to an overutilization of main memory on the compute nodes. Our research focuses on the parallel implementation of the set similarity join (SSJ) operator. This operator finds all pairs of records which have a similarity above a defined threshold using a similarity measure such as Jaccard. Our goal is a robust approach for executing SSJ that does not over-utilize memory and exploits CPU parallelization as much as possible. This approach requires data sharing between tasks/threads which is not foreseen in HPCC Systems so far. In this talk, we describe how we implemented multithreaded user-defined functions for the SSJ operator. To be able to control NUMAspecific parallelization conditions, we implemented a C++ plugin for HPCC Systems. Furthermore, we show how we visualized the relevant system parameters (CPU and memory usage). This talk is intended for anyone interested in extending HPCC Systems by plugins and monitoring distributed program execution.
Leveraging Intra-Node Parallelization in HPCC Systems
Leveraging Intra-Node Parallelization in HPCC Systems
HPCC Systems
DataPatterns.Profile() has been evolving since the last time you may have seen it. It does more. It looks better. It has been integrated into the ECL standard library and into ECL Watch. Learn what this data profiler can do for you and how its built-in visualization easily summarizes the results.
DataPatterns - Profiling in ECL Watch
DataPatterns - Profiling in ECL Watch
HPCC Systems
Join us for an introductory walk-through of using the Spark-HPCC Systems ecosystem to analyze your HPCC Systems data using a collaborative Apache Zeppelin notebook environment.
Leveraging the Spark-HPCC Ecosystem
Leveraging the Spark-HPCC Ecosystem
HPCC Systems
The Workunit Analyser examines the entire workunit to produce advice that both novices and experienced ECL developers should find useful. The Workunit Analyser is a post-execution analyser that identifies potential issues and assists users in writing better ECL.
Work Unit Analysis Tool
Work Unit Analysis Tool
HPCC Systems
Let's congratulate the winners of the 2019 HPCC Systems Poster Competition and other award recipients.
Community Award Ceremony
Community Award Ceremony
HPCC Systems
Have you ever written a long project for a simple column rename and thought, this should be easier? What about nicely named output statements? Yeah they bother me too. Oh, and DEDUP(SORT(DISTINCT()))? There is a better way! Learn how Dapper can help!
Dapper Tool - A Bundle to Make your ECL Neater
Dapper Tool - A Bundle to Make your ECL Neater
HPCC Systems
Join NSU University School student and program leader for girls in robotics, Ronnie Shashoua, as she talks about Gadget Girls - a project in collaboration with the NSU Alvin Sherman Library, NSU University School, the South Florida Girl Scouts, and sponsorship from the HPCC Systems Academic Program. Gadget Girls is a program aimed at encouraging girls in fourth and fifth grade to explore their interests in and love for STEM, especially robotics and engineering. Shashoua will discuss the underrepresentation of girls in the Florida Vex Robotics circuit, such as how it demonstrates a larger trend of low numbers of women undertaking STEM educational and career paths and the role it played in inspiring the creation of Gadget Girls.
A Success Story of Challenging the Status Quo: Gadget Girls and the Inclusion...
A Success Story of Challenging the Status Quo: Gadget Girls and the Inclusion...
HPCC Systems
Hear how the Florida Atlantic University Center for Autism and Related Disabilities has partnered with the HPCC Systems community to provide young people with autism both the technology and professional skills needed to compete in today’s workplace. Mentoring and hands-on coding through ECL workshops have positively impacted students, opening doors to new opportunities for both students and employers.
Beyond the Spectrum – Creating an Environment of Diversity and Empowerment wi...
Beyond the Spectrum – Creating an Environment of Diversity and Empowerment wi...
HPCC Systems
Text cleaning is becoming an essential step in text classification. Stop word removal is a crucial space-saving technique in text cleaning which saves huge amounts of space in text indexing. There are many domain-based common words which differ from one domain to another and have no value within a particular domain. Eliminating these words will reduce the size of the corpus and enhance the performance of text mining. This talk will discuss how the text vectors bundle, (CBOW), in HPCC Systems was used to find the domain based common words, and the methodology applied to enhance the performance of classification methods.
Using High Dimensional Representation of Words (CBOW) to Find Domain Based Co...
Using High Dimensional Representation of Words (CBOW) to Find Domain Based Co...
HPCC Systems
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Contenu connexe
Plus de HPCC Systems
Presented at the RV College of Engineering Multidisciplinary Trends in Information Technology, July 21 - 25, 2020.
Natural Language to SQL Query conversion using Machine Learning Techniques on...
Natural Language to SQL Query conversion using Machine Learning Techniques on...
HPCC Systems
Presented at the IEEE-RVCE Computer Society Webinar Series
Improving Efficiency of Machine Learning Algorithms using HPCC Systems
Improving Efficiency of Machine Learning Algorithms using HPCC Systems
HPCC Systems
Xian Yang's presentation to ODSC Europe 2019. Yang is a research fellow in the Data Science Institute at Imperial College London.
Towards Trustable AI for Complex Systems
Towards Trustable AI for Complex Systems
HPCC Systems
Closing / Adjourn
Closing / Adjourn
Closing / Adjourn
HPCC Systems
The reveal of how HPCC Systems is improving and expanding around the world for building a global community.
Community Website: Virtual Ribbon Cutting
Community Website: Virtual Ribbon Cutting
HPCC Systems
Come hear a brief overview on the direction the HPCC Systems platform is heading, and get a glimpse into some of the likely highlights included in the next minor and major versions.
Path to 8.0
Path to 8.0
HPCC Systems
This talk will explain the reasoning behind the release cycle changes, and how overcoming the challenges faced in the previous practice of automated testing has introduced new benefits and wider acceptance from the wider community.
Release Cycle Changes
Release Cycle Changes
HPCC Systems
An introductory look at the ECL H3 Plugin (available since v7.2.0) - a journey from lat/long to ROXIE Service driven visualizations
Geohashing with Uber’s H3 Geospatial Index
Geohashing with Uber’s H3 Geospatial Index
HPCC Systems
This presentation will provide an overview of the latest advancements in Machine Learning modules over the past year, including Clustering, Natural Language Processing, Deep Learning, and the Expanded Model Evaluation Metrics. Clustering Methods of the HPCC Systems Machine Learning Library The clustering method is an important part of unsupervised learning. To gain the unsupervised learning capability, two widely applied clustering methods, KMeans and DBSCAN are adopted to the current Machine Learning library. This presentation will introduce the newly developed clustering algorithms and the evaluation methods.
Advancements in HPCC Systems Machine Learning
Advancements in HPCC Systems Machine Learning
HPCC Systems
Learn how to package the HPCC Systems Platform in a Docker container and deploy it locally, and build an HPCC Systems Platform AMI followed by an AWS deployment.
Docker Support
Docker Support
HPCC Systems
The training process for modern deep neural networks requires big data and large computational power. Though HPCC Systems excels at both of these, HPCC Systems is limited to utilizing the CPU only. It has been shown that GPU acceleration vastly improves Deep Learning training time. In this talk, Robert will explain how HPCC Systems became the first GPU accelerated library while also greatly expanding its deep neural network capabilities.
Expanding HPCC Systems Deep Neural Network Capabilities
Expanding HPCC Systems Deep Neural Network Capabilities
HPCC Systems
HPCC Systems offers parallelization by assuming data-independent tasks. For operations having complex predicates, such as the set similarity join (SSJ) predicates, this assumption might create a tradeoff. On the one hand, one may choose a data replication strategy with large intermediate data groups assuring that all intermediate results fit into main memory. However, this can lead to an underutilization of today's massively parallel CPUs. On the other hand, you may choose a higher degree of replication for better CPU utilization. Such a choice may lead to an overutilization of main memory on the compute nodes. Our research focuses on the parallel implementation of the set similarity join (SSJ) operator. This operator finds all pairs of records which have a similarity above a defined threshold using a similarity measure such as Jaccard. Our goal is a robust approach for executing SSJ that does not over-utilize memory and exploits CPU parallelization as much as possible. This approach requires data sharing between tasks/threads which is not foreseen in HPCC Systems so far. In this talk, we describe how we implemented multithreaded user-defined functions for the SSJ operator. To be able to control NUMAspecific parallelization conditions, we implemented a C++ plugin for HPCC Systems. Furthermore, we show how we visualized the relevant system parameters (CPU and memory usage). This talk is intended for anyone interested in extending HPCC Systems by plugins and monitoring distributed program execution.
Leveraging Intra-Node Parallelization in HPCC Systems
Leveraging Intra-Node Parallelization in HPCC Systems
HPCC Systems
DataPatterns.Profile() has been evolving since the last time you may have seen it. It does more. It looks better. It has been integrated into the ECL standard library and into ECL Watch. Learn what this data profiler can do for you and how its built-in visualization easily summarizes the results.
DataPatterns - Profiling in ECL Watch
DataPatterns - Profiling in ECL Watch
HPCC Systems
Join us for an introductory walk-through of using the Spark-HPCC Systems ecosystem to analyze your HPCC Systems data using a collaborative Apache Zeppelin notebook environment.
Leveraging the Spark-HPCC Ecosystem
Leveraging the Spark-HPCC Ecosystem
HPCC Systems
The Workunit Analyser examines the entire workunit to produce advice that both novices and experienced ECL developers should find useful. The Workunit Analyser is a post-execution analyser that identifies potential issues and assists users in writing better ECL.
Work Unit Analysis Tool
Work Unit Analysis Tool
HPCC Systems
Let's congratulate the winners of the 2019 HPCC Systems Poster Competition and other award recipients.
Community Award Ceremony
Community Award Ceremony
HPCC Systems
Have you ever written a long project for a simple column rename and thought, this should be easier? What about nicely named output statements? Yeah they bother me too. Oh, and DEDUP(SORT(DISTINCT()))? There is a better way! Learn how Dapper can help!
Dapper Tool - A Bundle to Make your ECL Neater
Dapper Tool - A Bundle to Make your ECL Neater
HPCC Systems
Join NSU University School student and program leader for girls in robotics, Ronnie Shashoua, as she talks about Gadget Girls - a project in collaboration with the NSU Alvin Sherman Library, NSU University School, the South Florida Girl Scouts, and sponsorship from the HPCC Systems Academic Program. Gadget Girls is a program aimed at encouraging girls in fourth and fifth grade to explore their interests in and love for STEM, especially robotics and engineering. Shashoua will discuss the underrepresentation of girls in the Florida Vex Robotics circuit, such as how it demonstrates a larger trend of low numbers of women undertaking STEM educational and career paths and the role it played in inspiring the creation of Gadget Girls.
A Success Story of Challenging the Status Quo: Gadget Girls and the Inclusion...
A Success Story of Challenging the Status Quo: Gadget Girls and the Inclusion...
HPCC Systems
Hear how the Florida Atlantic University Center for Autism and Related Disabilities has partnered with the HPCC Systems community to provide young people with autism both the technology and professional skills needed to compete in today’s workplace. Mentoring and hands-on coding through ECL workshops have positively impacted students, opening doors to new opportunities for both students and employers.
Beyond the Spectrum – Creating an Environment of Diversity and Empowerment wi...
Beyond the Spectrum – Creating an Environment of Diversity and Empowerment wi...
HPCC Systems
Text cleaning is becoming an essential step in text classification. Stop word removal is a crucial space-saving technique in text cleaning which saves huge amounts of space in text indexing. There are many domain-based common words which differ from one domain to another and have no value within a particular domain. Eliminating these words will reduce the size of the corpus and enhance the performance of text mining. This talk will discuss how the text vectors bundle, (CBOW), in HPCC Systems was used to find the domain based common words, and the methodology applied to enhance the performance of classification methods.
Using High Dimensional Representation of Words (CBOW) to Find Domain Based Co...
Using High Dimensional Representation of Words (CBOW) to Find Domain Based Co...
HPCC Systems
Plus de HPCC Systems
(20)
Natural Language to SQL Query conversion using Machine Learning Techniques on...
Natural Language to SQL Query conversion using Machine Learning Techniques on...
Improving Efficiency of Machine Learning Algorithms using HPCC Systems
Improving Efficiency of Machine Learning Algorithms using HPCC Systems
Towards Trustable AI for Complex Systems
Towards Trustable AI for Complex Systems
Closing / Adjourn
Closing / Adjourn
Community Website: Virtual Ribbon Cutting
Community Website: Virtual Ribbon Cutting
Path to 8.0
Path to 8.0
Release Cycle Changes
Release Cycle Changes
Geohashing with Uber’s H3 Geospatial Index
Geohashing with Uber’s H3 Geospatial Index
Advancements in HPCC Systems Machine Learning
Advancements in HPCC Systems Machine Learning
Docker Support
Docker Support
Expanding HPCC Systems Deep Neural Network Capabilities
Expanding HPCC Systems Deep Neural Network Capabilities
Leveraging Intra-Node Parallelization in HPCC Systems
Leveraging Intra-Node Parallelization in HPCC Systems
DataPatterns - Profiling in ECL Watch
DataPatterns - Profiling in ECL Watch
Leveraging the Spark-HPCC Ecosystem
Leveraging the Spark-HPCC Ecosystem
Work Unit Analysis Tool
Work Unit Analysis Tool
Community Award Ceremony
Community Award Ceremony
Dapper Tool - A Bundle to Make your ECL Neater
Dapper Tool - A Bundle to Make your ECL Neater
A Success Story of Challenging the Status Quo: Gadget Girls and the Inclusion...
A Success Story of Challenging the Status Quo: Gadget Girls and the Inclusion...
Beyond the Spectrum – Creating an Environment of Diversity and Empowerment wi...
Beyond the Spectrum – Creating an Environment of Diversity and Empowerment wi...
Using High Dimensional Representation of Words (CBOW) to Find Domain Based Co...
Using High Dimensional Representation of Words (CBOW) to Find Domain Based Co...
Dernier
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Top profile Call Girls In Chandrapur [ 7014168258 ] Call Me For Genuine Model...
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Discover how TrafficWave Generator can drive targeted, engaging visitors to your online assets and propel your business to new heights. Unlock the power of free, set-and-forget traffic today. Featuring a user-friendly interface, set-and-forget functionality, and the ability to monetize the traffic with your affiliate links or product offers, TrafficWave Generator is a game-changer for online entrepreneurs, bloggers, and e-commerce store owners alike. Backed by a 30-day money-back guarantee and comprehensive bonus offerings, this software has the potential to transform your traffic-generation and content-creation efforts, unlocking new levels of success in the digital marketing landscape.
TrafficWave Generator Will Instantly drive targeted and engaging traffic back...
TrafficWave Generator Will Instantly drive targeted and engaging traffic back...
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Context 1. Housing Agent collected resale prices on HDB apartments in Singapore. Objective 2. To predict resale prices in to advise his potential clients. Strategies 3. Explore & Clean data for analysis. 4. Perform K-Means Clustering, in Orange, to find possible segments in the customer data. 5. Tune the model to improve its performance. 6. Visualise the findings, share conclusions, and give insight-driven recommendations. Author: Anthony mok Date: 18 Nov 2023 Email: xxiaohao@yahoo.com
Predicting HDB Resale Prices - Conducting Linear Regression Analysis With Orange
Predicting HDB Resale Prices - Conducting Linear Regression Analysis With Orange
ThinkInnovation
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