際際滷shows by User: bnajlis / http://www.slideshare.net/images/logo.gif 際際滷shows by User: bnajlis / Sun, 27 May 2018 16:26:27 GMT 際際滷Share feed for 際際滷shows by User: bnajlis Named Entity Recognition from Online News /slideshow/named-entity-recognition-from-online-news-99062761/99062761 namedentityextractionfromonlinenews-180527162627
This project aimed to create a series of models for the extraction of Named Entities (People, Locations, Organizations, Dates) from news headlines obtained online. We created two models: a traditional Natural Processing Language Model using Maximum Entropy , and a Deep Neural Network Model using pre-trained word embeddings. Accuracy results of both models show similar performance, but the requirements and limitations of both models are different and can help determine what type of model is best suited for each specific use case]]>

This project aimed to create a series of models for the extraction of Named Entities (People, Locations, Organizations, Dates) from news headlines obtained online. We created two models: a traditional Natural Processing Language Model using Maximum Entropy , and a Deep Neural Network Model using pre-trained word embeddings. Accuracy results of both models show similar performance, but the requirements and limitations of both models are different and can help determine what type of model is best suited for each specific use case]]>
Sun, 27 May 2018 16:26:27 GMT /slideshow/named-entity-recognition-from-online-news-99062761/99062761 bnajlis@slideshare.net(bnajlis) Named Entity Recognition from Online News bnajlis This project aimed to create a series of models for the extraction of Named Entities (People, Locations, Organizations, Dates) from news headlines obtained online. We created two models: a traditional Natural Processing Language Model using Maximum Entropy , and a Deep Neural Network Model using pre-trained word embeddings. Accuracy results of both models show similar performance, but the requirements and limitations of both models are different and can help determine what type of model is best suited for each specific use case <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/namedentityextractionfromonlinenews-180527162627-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This project aimed to create a series of models for the extraction of Named Entities (People, Locations, Organizations, Dates) from news headlines obtained online. We created two models: a traditional Natural Processing Language Model using Maximum Entropy , and a Deep Neural Network Model using pre-trained word embeddings. Accuracy results of both models show similar performance, but the requirements and limitations of both models are different and can help determine what type of model is best suited for each specific use case
Named Entity Recognition from Online News from Bernardo Najlis
]]>
2210 4 https://cdn.slidesharecdn.com/ss_thumbnails/namedentityextractionfromonlinenews-180527162627-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
Named Entity Recognition from Online News /slideshow/named-entity-recognition-from-online-news/99062562 ds8008-group3projectreport-180527162426
This project aimed to create a series of models for the extraction of Named Entities (People, Locations, Organizations, Dates) from news headlines obtained online. We created two models: a traditional Natural Processing Language Model using Maximum Entropy , and a Deep Neural Network Model using pre-trained word embeddings. Accuracy results of both models show similar performance, but the requirements and limitations of both models are different and can help determine what type of model is best suited for each specific use case.]]>

This project aimed to create a series of models for the extraction of Named Entities (People, Locations, Organizations, Dates) from news headlines obtained online. We created two models: a traditional Natural Processing Language Model using Maximum Entropy , and a Deep Neural Network Model using pre-trained word embeddings. Accuracy results of both models show similar performance, but the requirements and limitations of both models are different and can help determine what type of model is best suited for each specific use case.]]>
Sun, 27 May 2018 16:24:26 GMT /slideshow/named-entity-recognition-from-online-news/99062562 bnajlis@slideshare.net(bnajlis) Named Entity Recognition from Online News bnajlis This project aimed to create a series of models for the extraction of Named Entities (People, Locations, Organizations, Dates) from news headlines obtained online. We created two models: a traditional Natural Processing Language Model using Maximum Entropy , and a Deep Neural Network Model using pre-trained word embeddings. Accuracy results of both models show similar performance, but the requirements and limitations of both models are different and can help determine what type of model is best suited for each specific use case. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ds8008-group3projectreport-180527162426-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This project aimed to create a series of models for the extraction of Named Entities (People, Locations, Organizations, Dates) from news headlines obtained online. We created two models: a traditional Natural Processing Language Model using Maximum Entropy , and a Deep Neural Network Model using pre-trained word embeddings. Accuracy results of both models show similar performance, but the requirements and limitations of both models are different and can help determine what type of model is best suited for each specific use case.
Named Entity Recognition from Online News from Bernardo Najlis
]]>
2015 4 https://cdn.slidesharecdn.com/ss_thumbnails/ds8008-group3projectreport-180527162426-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0
Investment Fund Analytics /slideshow/investment-fund-analytics/77386815 ds8004-group1project-report-170630004139
A Data Science Project using data mining techniques (N-Grams, TF-IDF text analytics, sentiment detection) combined with R and ggplot2 for exploratory data analysis to predict stock market trends based on world news events sourced from Reddit /r/worldnews using Decision Trees and SVM (Support Vector Machines) on KNIME. All experiments were done using public cloud infrastructure, running HIVE queries to prefilter data with HDInsights on Azure.]]>

A Data Science Project using data mining techniques (N-Grams, TF-IDF text analytics, sentiment detection) combined with R and ggplot2 for exploratory data analysis to predict stock market trends based on world news events sourced from Reddit /r/worldnews using Decision Trees and SVM (Support Vector Machines) on KNIME. All experiments were done using public cloud infrastructure, running HIVE queries to prefilter data with HDInsights on Azure.]]>
Fri, 30 Jun 2017 00:41:39 GMT /slideshow/investment-fund-analytics/77386815 bnajlis@slideshare.net(bnajlis) Investment Fund Analytics bnajlis A Data Science Project using data mining techniques (N-Grams, TF-IDF text analytics, sentiment detection) combined with R and ggplot2 for exploratory data analysis to predict stock market trends based on world news events sourced from Reddit /r/worldnews using Decision Trees and SVM (Support Vector Machines) on KNIME. All experiments were done using public cloud infrastructure, running HIVE queries to prefilter data with HDInsights on Azure. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ds8004-group1project-report-170630004139-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A Data Science Project using data mining techniques (N-Grams, TF-IDF text analytics, sentiment detection) combined with R and ggplot2 for exploratory data analysis to predict stock market trends based on world news events sourced from Reddit /r/worldnews using Decision Trees and SVM (Support Vector Machines) on KNIME. All experiments were done using public cloud infrastructure, running HIVE queries to prefilter data with HDInsights on Azure.
Investment Fund Analytics from Bernardo Najlis
]]>
2495 10 https://cdn.slidesharecdn.com/ss_thumbnails/ds8004-group1project-report-170630004139-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0
Social Media World News Impact on Stock Index Values - Investment Fund Analytics - Data Mining Project /slideshow/social-media-world-news-impact-on-stock-index-values-investment-fund-analytics-data-mining-project/75328657 ds8004-groupproject-finalpresentation-170423195825
Presentation for project on Social Media World News Impact on Stock Index Values (DJIA) for Investment Fund Analytics. Group project done in course DS8004 - Data Mining at Ryerson University for Masters in Data Science and Analytics.]]>

Presentation for project on Social Media World News Impact on Stock Index Values (DJIA) for Investment Fund Analytics. Group project done in course DS8004 - Data Mining at Ryerson University for Masters in Data Science and Analytics.]]>
Sun, 23 Apr 2017 19:58:25 GMT /slideshow/social-media-world-news-impact-on-stock-index-values-investment-fund-analytics-data-mining-project/75328657 bnajlis@slideshare.net(bnajlis) Social Media World News Impact on Stock Index Values - Investment Fund Analytics - Data Mining Project bnajlis Presentation for project on Social Media World News Impact on Stock Index Values (DJIA) for Investment Fund Analytics. Group project done in course DS8004 - Data Mining at Ryerson University for Masters in Data Science and Analytics. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ds8004-groupproject-finalpresentation-170423195825-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation for project on Social Media World News Impact on Stock Index Values (DJIA) for Investment Fund Analytics. Group project done in course DS8004 - Data Mining at Ryerson University for Masters in Data Science and Analytics.
Social Media World News Impact on Stock Index Values - Investment Fund Analytics - Data Mining Project from Bernardo Najlis
]]>
2789 8 https://cdn.slidesharecdn.com/ss_thumbnails/ds8004-groupproject-finalpresentation-170423195825-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
Social Media Analytics on Canadian Airlines /bnajlis/social-media-analytics-on-canadian-airlines ds8006-groupproject-presentation-170423194839
A research project using Twitter on Canadian Airlines: Topic Modelling, Sentiment Detection and Network Analytics. Presented on April 5th, 2017 in Toronto as part of course DS8006 - Social Media Analytics at Ryerson Masters in Data Science and Analytics.]]>

A research project using Twitter on Canadian Airlines: Topic Modelling, Sentiment Detection and Network Analytics. Presented on April 5th, 2017 in Toronto as part of course DS8006 - Social Media Analytics at Ryerson Masters in Data Science and Analytics.]]>
Sun, 23 Apr 2017 19:48:39 GMT /bnajlis/social-media-analytics-on-canadian-airlines bnajlis@slideshare.net(bnajlis) Social Media Analytics on Canadian Airlines bnajlis A research project using Twitter on Canadian Airlines: Topic Modelling, Sentiment Detection and Network Analytics. Presented on April 5th, 2017 in Toronto as part of course DS8006 - Social Media Analytics at Ryerson Masters in Data Science and Analytics. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ds8006-groupproject-presentation-170423194839-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A research project using Twitter on Canadian Airlines: Topic Modelling, Sentiment Detection and Network Analytics. Presented on April 5th, 2017 in Toronto as part of course DS8006 - Social Media Analytics at Ryerson Masters in Data Science and Analytics.
Social Media Analytics on Canadian Airlines from Bernardo Najlis
]]>
965 8 https://cdn.slidesharecdn.com/ss_thumbnails/ds8006-groupproject-presentation-170423194839-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
#FluxFlow /slideshow/fluxflow/72315295 fluxflow-170218234617
#FluxFlow is a Social Media Analytics visualization to help understand the spread and behavior of anomalous information. Presented in DS8006 - Social Media Analytics course for the Masters in Data Science and Analytics program on February 1st, 2017 at Ryerson University.]]>

#FluxFlow is a Social Media Analytics visualization to help understand the spread and behavior of anomalous information. Presented in DS8006 - Social Media Analytics course for the Masters in Data Science and Analytics program on February 1st, 2017 at Ryerson University.]]>
Sat, 18 Feb 2017 23:46:16 GMT /slideshow/fluxflow/72315295 bnajlis@slideshare.net(bnajlis) #FluxFlow bnajlis #FluxFlow is a Social Media Analytics visualization to help understand the spread and behavior of anomalous information. Presented in DS8006 - Social Media Analytics course for the Masters in Data Science and Analytics program on February 1st, 2017 at Ryerson University. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/fluxflow-170218234617-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> #FluxFlow is a Social Media Analytics visualization to help understand the spread and behavior of anomalous information. Presented in DS8006 - Social Media Analytics course for the Masters in Data Science and Analytics program on February 1st, 2017 at Ryerson University.
#FluxFlow from Bernardo Najlis
]]>
2250 3 https://cdn.slidesharecdn.com/ss_thumbnails/fluxflow-170218234617-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
Introduction to knime /bnajlis/introduction-to-knime introductiontoknime-170218233726
Brief introduction to KNIME, an open source data analytics and blending tool for data mining and data science.]]>

Brief introduction to KNIME, an open source data analytics and blending tool for data mining and data science.]]>
Sat, 18 Feb 2017 23:37:26 GMT /bnajlis/introduction-to-knime bnajlis@slideshare.net(bnajlis) Introduction to knime bnajlis Brief introduction to KNIME, an open source data analytics and blending tool for data mining and data science. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoknime-170218233726-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Brief introduction to KNIME, an open source data analytics and blending tool for data mining and data science.
Introduction to knime from Bernardo Najlis
]]>
6960 5 https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoknime-170218233726-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
Toastmasters speech #7 - Research your Subject /slideshow/toastmasters-speech-7-research-your-subject-10517255/10517255 toastmastersspeech7-researchyoursubject-111208094925-phpapp02
]]>

]]>
Thu, 08 Dec 2011 09:49:25 GMT /slideshow/toastmasters-speech-7-research-your-subject-10517255/10517255 bnajlis@slideshare.net(bnajlis) Toastmasters speech #7 - Research your Subject bnajlis <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/toastmastersspeech7-researchyoursubject-111208094925-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br>
Toastmasters speech #7 - Research your Subject from Bernardo Najlis
]]>
13162 15 https://cdn.slidesharecdn.com/ss_thumbnails/toastmastersspeech7-researchyoursubject-111208094925-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds document White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0
Toastmasters project #5 - Just a jump /bnajlis/toastmasters-project-5-just-a-jump toastmastersproject5-justajump-111207161158-phpapp01
]]>

]]>
Wed, 07 Dec 2011 16:11:55 GMT /bnajlis/toastmasters-project-5-just-a-jump bnajlis@slideshare.net(bnajlis) Toastmasters project #5 - Just a jump bnajlis <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/toastmastersproject5-justajump-111207161158-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br>
Toastmasters project #5 - Just a jump from Bernardo Najlis
]]>
13591 3 https://cdn.slidesharecdn.com/ss_thumbnails/toastmastersproject5-justajump-111207161158-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds document White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0
What is lomography? /slideshow/what-is-lomography/10087146 whatislomography-111109080145-phpapp02
Project #8 of Toastmasters - Get Comfortable with visual aids]]>

Project #8 of Toastmasters - Get Comfortable with visual aids]]>
Wed, 09 Nov 2011 08:01:44 GMT /slideshow/what-is-lomography/10087146 bnajlis@slideshare.net(bnajlis) What is lomography? bnajlis Project #8 of Toastmasters - Get Comfortable with visual aids <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/whatislomography-111109080145-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Project #8 of Toastmasters - Get Comfortable with visual aids
What is lomography? from Bernardo Najlis
]]>
2962 7 https://cdn.slidesharecdn.com/ss_thumbnails/whatislomography-111109080145-phpapp02-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
Plethora /slideshow/plethora/7925632 plethora-110511101359-phpapp02
Toasmaster's Word of the Day for my Grammarian Role]]>

Toasmaster's Word of the Day for my Grammarian Role]]>
Wed, 11 May 2011 10:13:59 GMT /slideshow/plethora/7925632 bnajlis@slideshare.net(bnajlis) Plethora bnajlis Toasmaster's Word of the Day for my Grammarian Role <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/plethora-110511101359-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Toasmaster&#39;s Word of the Day for my Grammarian Role
Plethora from Bernardo Najlis
]]>
1683 2 https://cdn.slidesharecdn.com/ss_thumbnails/plethora-110511101359-phpapp02-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
Business Intelligence Presentation - Data Mining (2/2) /slideshow/business-intelligence-presentation-4642055/4642055 businessintelligencepresentation-part2-100629085340-phpapp02
In this second part of the Business Intelligence Presentation, we dive into Data Mining, what it is, its business applications and some CRM related examples.]]>

In this second part of the Business Intelligence Presentation, we dive into Data Mining, what it is, its business applications and some CRM related examples.]]>
Tue, 29 Jun 2010 08:53:20 GMT /slideshow/business-intelligence-presentation-4642055/4642055 bnajlis@slideshare.net(bnajlis) Business Intelligence Presentation - Data Mining (2/2) bnajlis In this second part of the Business Intelligence Presentation, we dive into Data Mining, what it is, its business applications and some CRM related examples. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/businessintelligencepresentation-part2-100629085340-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this second part of the Business Intelligence Presentation, we dive into Data Mining, what it is, its business applications and some CRM related examples.
Business Intelligence Presentation - Data Mining (2/2) from Bernardo Najlis
]]>
2791 4 https://cdn.slidesharecdn.com/ss_thumbnails/businessintelligencepresentation-part2-100629085340-phpapp02-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
Business Intelligence Presentation (1/2) /slideshow/business-intelligence-presentation-12/4641780 businessintelligencepresentation-100629081536-phpapp01
Business Intelligence made easy! This is the first part of a two-part presentation I prepared for one of our customers to help them understand what Business Intelligence is and what can it do...]]>

Business Intelligence made easy! This is the first part of a two-part presentation I prepared for one of our customers to help them understand what Business Intelligence is and what can it do...]]>
Tue, 29 Jun 2010 08:15:29 GMT /slideshow/business-intelligence-presentation-12/4641780 bnajlis@slideshare.net(bnajlis) Business Intelligence Presentation (1/2) bnajlis Business Intelligence made easy! This is the first part of a two-part presentation I prepared for one of our customers to help them understand what Business Intelligence is and what can it do... <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/businessintelligencepresentation-100629081536-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Business Intelligence made easy! This is the first part of a two-part presentation I prepared for one of our customers to help them understand what Business Intelligence is and what can it do...
Business Intelligence Presentation (1/2) from Bernardo Najlis
]]>
59055 50 https://cdn.slidesharecdn.com/ss_thumbnails/businessintelligencepresentation-100629081536-phpapp01-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-bnajlis-48x48.jpg?cb=1715202063 Senior Architect specialized in Business Intelligence, Data Analytics and technology+business related projects. Professionally motivated by the application of Information Technologies in the Business Analysis area to increase companies performance using Data Warehousing and Machine Learning. Robust mix of technology expertise and business skills, focused on technology application to obtain specific business results. 15+ years of working experience with customers of various sizes and sectors. 8+ years of client-facing experience working at consulting services organizations. Entrepreneurial spirit leading the start-up and management of three consulting companies. Worked successfully in di... bernardonajlis.wordpress.com https://cdn.slidesharecdn.com/ss_thumbnails/namedentityextractionfromonlinenews-180527162627-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/named-entity-recognition-from-online-news-99062761/99062761 Named Entity Recogniti... https://cdn.slidesharecdn.com/ss_thumbnails/ds8008-group3projectreport-180527162426-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/named-entity-recognition-from-online-news/99062562 Named Entity Recogniti... https://cdn.slidesharecdn.com/ss_thumbnails/ds8004-group1project-report-170630004139-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/investment-fund-analytics/77386815 Investment Fund Analytics