�ݺ�ߣshows by User: BenjaminTaylor4

�ݺ�ߣshows by User: BenjaminTaylor4 / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: BenjaminTaylor4 / Mon, 02 May 2016 17:37:53 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: BenjaminTaylor4 Using Deep Learning And NLP To Predict Performance From Resumes /slideshow/using-deep-learning-and-nlp-to-predict-performance-from-resumes/61588580 siopf-160502173753
Master tutorial on resume modeling given at SIOP 2016 in California. Please let me know if you have any questions on this topic. Using NLP can be very powerful for predicting candidate performance but it can also be dangerous if adverse impact is not considered from the beginning. ]]>
Master tutorial on resume modeling given at SIOP 2016 in California. Please let me know if you have any questions on this topic. Using NLP can be very powerful for predicting candidate performance but it can also be dangerous if adverse impact is not considered from the beginning. ]]> Mon, 02 May 2016 17:37:53 GMT /slideshow/using-deep-learning-and-nlp-to-predict-performance-from-resumes/61588580 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) Using Deep Learning And NLP To Predict Performance From Resumes BenjaminTaylor4 Master tutorial on resume modeling given at SIOP 2016 in California. Please let me know if you have any questions on this topic. Using NLP can be very powerful for predicting candidate performance but it can also be dangerous if adverse impact is not considered from the beginning. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/siopf-160502173753-thumbnail.jpg?width=120&height=120&fit=bounds" /> Master tutorial on resume modeling given at SIOP 2016 in California. Please let me know if you have any questions on this topic. Using NLP can be very powerful for predicting candidate performance but it can also be dangerous if adverse impact is not considered from the beginning.

Using Deep Learning And NLP To Predict Performance From Resumes from Benjamin Taylor

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0 Deep learning for_devs /slideshow/deep-learning-fordevs/60761550 deeplearningfordevs-160411145734
Deep learning with the developer in ming]]>
Deep learning with the developer in ming]]> Mon, 11 Apr 2016 14:57:34 GMT /slideshow/deep-learning-fordevs/60761550 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) Deep learning for_devs BenjaminTaylor4 Deep learning with the developer in ming <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/deeplearningfordevs-160411145734-thumbnail.jpg?width=120&height=120&fit=bounds" /> Deep learning with the developer in ming

Deep learning for_devs from Benjamin Taylor

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0 Predicting Candidate Performance From Text NLP /slideshow/predicting-candidate-performance-from-text-nlp/60530841 taylorben1-160405231216
This is a talk I gave at PACON. Using text to predict candidate / applicant performance based on historical data. Introduction to natural language processing and deep learning. This can also be used for social media profiling (Facebook), Twitter, Assessment, essay, and resume. Text analytics is much easier than most people thing. ]]>
This is a talk I gave at PACON. Using text to predict candidate / applicant performance based on historical data. Introduction to natural language processing and deep learning. This can also be used for social media profiling (Facebook), Twitter, Assessment, essay, and resume. Text analytics is much easier than most people thing. ]]> Tue, 05 Apr 2016 23:12:16 GMT /slideshow/predicting-candidate-performance-from-text-nlp/60530841 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) Predicting Candidate Performance From Text NLP BenjaminTaylor4 This is a talk I gave at PACON. Using text to predict candidate / applicant performance based on historical data. Introduction to natural language processing and deep learning. This can also be used for social media profiling (Facebook), Twitter, Assessment, essay, and resume. Text analytics is much easier than most people thing. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/taylorben1-160405231216-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is a talk I gave at PACON. Using text to predict candidate / applicant performance based on historical data. Introduction to natural language processing and deep learning. This can also be used for social media profiling (Facebook), Twitter, Assessment, essay, and resume. Text analytics is much easier than most people thing.

Predicting Candidate Performance From Text NLP from Benjamin Taylor

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0 Python genetics /slideshow/python-genetics/60530625 flashpresentation1-160405230145
Gave this talk on python genetics at HireVue for a flash presentation. What does this have to do with SAAS? Datascience? Machine learning? Nothing.... :) HireVue.com has a fun work culture]]>
Gave this talk on python genetics at HireVue for a flash presentation. What does this have to do with SAAS? Datascience? Machine learning? Nothing.... :) HireVue.com has a fun work culture]]> Tue, 05 Apr 2016 23:01:44 GMT /slideshow/python-genetics/60530625 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) Python genetics BenjaminTaylor4 Gave this talk on python genetics at HireVue for a flash presentation. What does this have to do with SAAS? Datascience? Machine learning? Nothing.... :) HireVue.com has a fun work culture <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/flashpresentation1-160405230145-thumbnail.jpg?width=120&height=120&fit=bounds" /> Gave this talk on python genetics at HireVue for a flash presentation. What does this have to do with SAAS? Datascience? Machine learning? Nothing.... :) HireVue.com has a fun work culture

Python genetics from Benjamin Taylor

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0 Homeless story /slideshow/homeless-story/48061444 homelessstory-150512175527-lva1-app6891
Camping college student spends Logan winter living outside in 15 below weather]]>
Camping college student spends Logan winter living outside in 15 below weather]]> Tue, 12 May 2015 17:55:27 GMT /slideshow/homeless-story/48061444 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) Homeless story BenjaminTaylor4 Camping college student spends Logan winter living outside in 15 below weather <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/homelessstory-150512175527-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> Camping college student spends Logan winter living outside in 15 below weather

Homeless story from Benjamin Taylor

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0 #SIOP15 Presentation On Performance Sorting Using Video Interviews /slideshow/siop-12min-pdf/47879015 siop12minpdf-150507183507-lva1-app6892
This is a presentation I gave at SIOP 2015 in Philadelphia. The presentation shows how you can predict performance from a video interview using unstructured feature extraction and supervised learning. It also discusses k-folding cross validation which is less commonly known with in the IO community, but preferred within the data science community.]]>
This is a presentation I gave at SIOP 2015 in Philadelphia. The presentation shows how you can predict performance from a video interview using unstructured feature extraction and supervised learning. It also discusses k-folding cross validation which is less commonly known with in the IO community, but preferred within the data science community.]]> Thu, 07 May 2015 18:35:07 GMT /slideshow/siop-12min-pdf/47879015 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) #SIOP15 Presentation On Performance Sorting Using Video Interviews BenjaminTaylor4 This is a presentation I gave at SIOP 2015 in Philadelphia. The presentation shows how you can predict performance from a video interview using unstructured feature extraction and supervised learning. It also discusses k-folding cross validation which is less commonly known with in the IO community, but preferred within the data science community. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/siop12minpdf-150507183507-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is a presentation I gave at SIOP 2015 in Philadelphia. The presentation shows how you can predict performance from a video interview using unstructured feature extraction and supervised learning. It also discusses k-folding cross validation which is less commonly known with in the IO community, but preferred within the data science community.

#SIOP15 Presentation On Performance Sorting Using Video Interviews from Benjamin Taylor

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0 #SIOP15 Presentation on /slideshow/siop15-presentation-on/47878945 siop12min1-150507183312-lva1-app6892
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]]> Thu, 07 May 2015 18:33:12 GMT /slideshow/siop15-presentation-on/47878945 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) #SIOP15 Presentation on BenjaminTaylor4 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/siop12min1-150507183312-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" />

#SIOP15 Presentation on from Benjamin Taylor

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0 How To Model Text Like A Rockstar /slideshow/how-to-model-text-like-a-rockstar/47203354 spring2015bigmountaindata-150420112538-conversion-gate02
In this talk I talk about how to model text. I presented it at the spring 2015 big mountain data conference in Utah. The talk had a lengthy python notebook with it, so it may be less useful without that content.]]>
In this talk I talk about how to model text. I presented it at the spring 2015 big mountain data conference in Utah. The talk had a lengthy python notebook with it, so it may be less useful without that content.]]> Mon, 20 Apr 2015 11:25:38 GMT /slideshow/how-to-model-text-like-a-rockstar/47203354 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) How To Model Text Like A Rockstar BenjaminTaylor4 In this talk I talk about how to model text. I presented it at the spring 2015 big mountain data conference in Utah. The talk had a lengthy python notebook with it, so it may be less useful without that content. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/spring2015bigmountaindata-150420112538-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds" /> In this talk I talk about how to model text. I presented it at the spring 2015 big mountain data conference in Utah. The talk had a lengthy python notebook with it, so it may be less useful without that content.

How To Model Text Like A Rockstar from Benjamin Taylor

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0 Predictive analytics and big data tutorial /slideshow/prediction-tutorial-safe/37966230 predictiontutorialsafe-140813150450-phpapp02
This presentation covers data science buzz words, big data introduction, predictive analytics, and model building methods. Structured vs unstructured. Supervised learning vs unsupervised learning. ]]>
This presentation covers data science buzz words, big data introduction, predictive analytics, and model building methods. Structured vs unstructured. Supervised learning vs unsupervised learning. ]]> Wed, 13 Aug 2014 15:04:50 GMT /slideshow/prediction-tutorial-safe/37966230 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) Predictive analytics and big data tutorial BenjaminTaylor4 This presentation covers data science buzz words, big data introduction, predictive analytics, and model building methods. Structured vs unstructured. Supervised learning vs unsupervised learning. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/predictiontutorialsafe-140813150450-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> This presentation covers data science buzz words, big data introduction, predictive analytics, and model building methods. Structured vs unstructured. Supervised learning vs unsupervised learning.

Predictive analytics and big data tutorial from Benjamin Taylor

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0 How to simulate semiconductor yield /slideshow/how-to-simulate-semiconductor-yield/37469855 yieldsim-140729131905-phpapp02
How to simulate semiconductor die yield from a fab environment. A wafer never travels through the fab the same way because multiple tools exist for identical steps, and some tools have multiple chambers for processing. These are all called contexts, and each context has a different impact on yield. The challenge is to reverse the sources causing yield fall out with as few observations as possible. ]]>
How to simulate semiconductor die yield from a fab environment. A wafer never travels through the fab the same way because multiple tools exist for identical steps, and some tools have multiple chambers for processing. These are all called contexts, and each context has a different impact on yield. The challenge is to reverse the sources causing yield fall out with as few observations as possible. ]]> Tue, 29 Jul 2014 13:19:05 GMT /slideshow/how-to-simulate-semiconductor-yield/37469855 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) How to simulate semiconductor yield BenjaminTaylor4 How to simulate semiconductor die yield from a fab environment. A wafer never travels through the fab the same way because multiple tools exist for identical steps, and some tools have multiple chambers for processing. These are all called contexts, and each context has a different impact on yield. The challenge is to reverse the sources causing yield fall out with as few observations as possible. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/yieldsim-140729131905-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> How to simulate semiconductor die yield from a fab environment. A wafer never travels through the fab the same way because multiple tools exist for identical steps, and some tools have multiple chambers for processing. These are all called contexts, and each context has a different impact on yield. The challenge is to reverse the sources causing yield fall out with as few observations as possible.

How to simulate semiconductor yield from Benjamin Taylor

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0 Text analytics intro /slideshow/text-analytics-intro/36468936 textanalyticsintro-140630105414-phpapp01
This is a simple text analytics intro I put together for people with traditional numeric backgrounds that want to venture into text prediction. Some of this work came out of a competition that Skullcandy helped facilitate. ]]>
This is a simple text analytics intro I put together for people with traditional numeric backgrounds that want to venture into text prediction. Some of this work came out of a competition that Skullcandy helped facilitate. ]]> Mon, 30 Jun 2014 10:54:14 GMT /slideshow/text-analytics-intro/36468936 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) Text analytics intro BenjaminTaylor4 This is a simple text analytics intro I put together for people with traditional numeric backgrounds that want to venture into text prediction. Some of this work came out of a competition that Skullcandy helped facilitate. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/textanalyticsintro-140630105414-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is a simple text analytics intro I put together for people with traditional numeric backgrounds that want to venture into text prediction. Some of this work came out of a competition that Skullcandy helped facilitate.

Text analytics intro from Benjamin Taylor

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0 Utah, the greatest SMOG on earth. Harvesting data for air quality prediction /slideshow/utah-the-greatest-smog-on-earth-harvesting-data-for-air-quality-prediction/36117073 smognoficlean-140620122714-phpapp02
Utah, the greatest SMOG on earth. Harvesting data for air quality prediction. Presentation walks through simple data sources, data sources that required javascript packet gathering and scraping. Finally data sources that require reverse map to data conversions. ]]>
Utah, the greatest SMOG on earth. Harvesting data for air quality prediction. Presentation walks through simple data sources, data sources that required javascript packet gathering and scraping. Finally data sources that require reverse map to data conversions. ]]> Fri, 20 Jun 2014 12:27:14 GMT /slideshow/utah-the-greatest-smog-on-earth-harvesting-data-for-air-quality-prediction/36117073 BenjaminTaylor4@slideshare.net(BenjaminTaylor4) Utah, the greatest SMOG on earth. Harvesting data for air quality prediction BenjaminTaylor4 Utah, the greatest SMOG on earth. Harvesting data for air quality prediction. Presentation walks through simple data sources, data sources that required javascript packet gathering and scraping. Finally data sources that require reverse map to data conversions. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/smognoficlean-140620122714-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Utah, the greatest SMOG on earth. Harvesting data for air quality prediction. Presentation walks through simple data sources, data sources that required javascript packet gathering and scraping. Finally data sources that require reverse map to data conversions.

Utah, the greatest SMOG on earth. Harvesting data for air quality prediction from Benjamin Taylor

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0 https://cdn.slidesharecdn.com/profile-photo-BenjaminTaylor4-48x48.jpg?cb=1523429466 I am "cloud boy". I have had experience setting up large GPU compute clusters the manual way with ip tables, NFS mounts, ssh keys, ssh cloud configs scripts, service configs, and all of the unexpected troubleshooting that comes with that. It sucks. Now I have seen the light with virtual cloud solutions like AWS and I am in heaven! I can do what use to take me weeks in minutes. Need a 1000 node hadoop/cassandra/mysql cluster/sun grid/cluster? No problem! Need dynamic expansion/contraction? NO PROBLEM! Need a cloud AI optimizer? Oh wait, that doesn't exist yet... don't worry I am on it. My current passion is focused on my cloud optimization, HR analytics, and general prediction engines. ... http://www.metaheuristic.com https://cdn.slidesharecdn.com/ss_thumbnails/siopf-160502173753-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/using-deep-learning-and-nlp-to-predict-performance-from-resumes/61588580 Using Deep Learning An... https://cdn.slidesharecdn.com/ss_thumbnails/deeplearningfordevs-160411145734-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/deep-learning-fordevs/60761550 Deep learning for_devs https://cdn.slidesharecdn.com/ss_thumbnails/taylorben1-160405231216-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/predicting-candidate-performance-from-text-nlp/60530841 Predicting Candidate P...