ºÝºÝߣshows by User: alexip / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: alexip / Mon, 23 Oct 2017 15:19:37 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: alexip AWS Machine Learning Big Data NYC /slideshow/aws-machine-learning-big-data-nyc/81106818 alexisperrierglobalbigdatanycml171024-171023151937
Presentation of the AWS Machine Learning platform at the Global Big Data conference - NYC 2017 Oct 24 - Alexis Perrier]]>
Presentation of the AWS Machine Learning platform at the Global Big Data conference - NYC 2017 Oct 24 - Alexis Perrier]]> Mon, 23 Oct 2017 15:19:37 GMT /slideshow/aws-machine-learning-big-data-nyc/81106818 alexip@slideshare.net(alexip) AWS Machine Learning Big Data NYC alexip Presentation of the AWS Machine Learning platform at the Global Big Data conference - NYC 2017 Oct 24 - Alexis Perrier <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/alexisperrierglobalbigdatanycml171024-171023151937-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation of the AWS Machine Learning platform at the Global Big Data conference - NYC 2017 Oct 24 - Alexis Perrier
AWS Machine Learning Big Data NYC from Alexis Perrier
]]> 1026 3 https://cdn.slidesharecdn.com/ss_thumbnails/alexisperrierglobalbigdatanycml171024-171023151937-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 Cours de topic modeling https://fr.slideshare.net/slideshow/cours-de-topic-modeling/76630004 upem-topicmodeling-170604121319
Cours sur le topic modeling - UPEM - Master Méthode computationnelle et analyse de contenu I: Topic Modeling * Nature et applications * Approche Deterministe: LSA * Approche Probabiliste: LDA * Quelques librairies en R et python II: Le package STM en R * Parametres * Métriques: exclusivité et cohérence sémantique * Appliqué a un corpus propre LAB - R STM * Le corpus: résumés d'articles tech, IEEE et Arstechnica * Le package STM en R * Comment determiner le nombre optimal de topics? * Comment interpreter les résultats? * Jupyter Notebook et Script R III: forum Alt-right sur Facebook * 500.000 commentaires provenant du forum alt-right God Trump Emperor * De la nécessité de travailler le contenu * Filtrer le bruit avec * Lemmatization, tokenization * Part of Speech tagging * Named entity recognition * Jupyter Notebook et Script R IV: Application au Francais * Quelles sont les librairies pour: * Part of Speech * Tokenization * Lemmatization V: Resources * Articles et blogs ]]>
Cours sur le topic modeling - UPEM - Master Méthode computationnelle et analyse de contenu I: Topic Modeling * Nature et applications * Approche Deterministe: LSA * Approche Probabiliste: LDA * Quelques librairies en R et python II: Le package STM en R * Parametres * Métriques: exclusivité et cohérence sémantique * Appliqué a un corpus propre LAB - R STM * Le corpus: résumés d'articles tech, IEEE et Arstechnica * Le package STM en R * Comment determiner le nombre optimal de topics? * Comment interpreter les résultats? * Jupyter Notebook et Script R III: forum Alt-right sur Facebook * 500.000 commentaires provenant du forum alt-right God Trump Emperor * De la nécessité de travailler le contenu * Filtrer le bruit avec * Lemmatization, tokenization * Part of Speech tagging * Named entity recognition * Jupyter Notebook et Script R IV: Application au Francais * Quelles sont les librairies pour: * Part of Speech * Tokenization * Lemmatization V: Resources * Articles et blogs ]]> Sun, 04 Jun 2017 12:13:19 GMT https://fr.slideshare.net/slideshow/cours-de-topic-modeling/76630004 alexip@slideshare.net(alexip) Cours de topic modeling alexip Cours sur le topic modeling - UPEM - Master Méthode computationnelle et analyse de contenu I: Topic Modeling * Nature et applications * Approche Deterministe: LSA * Approche Probabiliste: LDA * Quelques librairies en R et python II: Le package STM en R * Parametres * Métriques: exclusivité et cohérence sémantique * Appliqué a un corpus propre LAB - R STM * Le corpus: résumés d'articles tech, IEEE et Arstechnica * Le package STM en R * Comment determiner le nombre optimal de topics? * Comment interpreter les résultats? * Jupyter Notebook et Script R III: forum Alt-right sur Facebook * 500.000 commentaires provenant du forum alt-right God Trump Emperor * De la nécessité de travailler le contenu * Filtrer le bruit avec * Lemmatization, tokenization * Part of Speech tagging * Named entity recognition * Jupyter Notebook et Script R IV: Application au Francais * Quelles sont les librairies pour: * Part of Speech * Tokenization * Lemmatization V: Resources * Articles et blogs <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/upem-topicmodeling-170604121319-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Cours sur le topic modeling - UPEM - Master Méthode computationnelle et analyse de contenu I: Topic Modeling * Nature et applications * Approche Deterministe: LSA * Approche Probabiliste: LDA * Quelques librairies en R et python II: Le package STM en R * Parametres * Métriques: exclusivité et cohérence sémantique * Appliqué a un corpus propre LAB - R STM * Le corpus: résumés d&#39;articles tech, IEEE et Arstechnica * Le package STM en R * Comment determiner le nombre optimal de topics? * Comment interpreter les résultats? * Jupyter Notebook et Script R III: forum Alt-right sur Facebook * 500.000 commentaires provenant du forum alt-right God Trump Emperor * De la nécessité de travailler le contenu * Filtrer le bruit avec * Lemmatization, tokenization * Part of Speech tagging * Named entity recognition * Jupyter Notebook et Script R IV: Application au Francais * Quelles sont les librairies pour: * Part of Speech * Tokenization * Lemmatization V: Resources * Articles et blogs
from Alexis Perrier
]]> 2670 10 https://cdn.slidesharecdn.com/ss_thumbnails/upem-topicmodeling-170604121319-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 Topic modeling of Twitter followers - Paris Machine Learning meetup - Alex Perrier https://fr.slideshare.net/slideshow/topic-modeling-of-twitter-followers-paris-machine-learning-meetup-alex-perrier/60133252 parismeetupslidestopicmodelingoftwitterfollowersalexperrier-bewitchedbymachinelearning-160328213711
Dans cette presentation je montre comment appliquer des techniques de topic modeling a un fil twitter en utilisant gensim, python et en comparant certains algorithmes: LSA, LSA ...]]>
Dans cette presentation je montre comment appliquer des techniques de topic modeling a un fil twitter en utilisant gensim, python et en comparant certains algorithmes: LSA, LSA ...]]> Mon, 28 Mar 2016 21:37:11 GMT https://fr.slideshare.net/slideshow/topic-modeling-of-twitter-followers-paris-machine-learning-meetup-alex-perrier/60133252 alexip@slideshare.net(alexip) Topic modeling of Twitter followers - Paris Machine Learning meetup - Alex Perrier alexip Dans cette presentation je montre comment appliquer des techniques de topic modeling a un fil twitter en utilisant gensim, python et en comparant certains algorithmes: LSA, LSA ... <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/parismeetupslidestopicmodelingoftwitterfollowersalexperrier-bewitchedbymachinelearning-160328213711-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Dans cette presentation je montre comment appliquer des techniques de topic modeling a un fil twitter en utilisant gensim, python et en comparant certains algorithmes: LSA, LSA ...
from Alexis Perrier
]]> 657 8 https://cdn.slidesharecdn.com/ss_thumbnails/parismeetupslidestopicmodelingoftwitterfollowersalexperrier-bewitchedbymachinelearning-160328213711-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 Large data with Scikit-learn - Boston Data Mining Meetup - Alex Perrier /alexip/large-data-with-scikitlearn-boston-data-mining-meetup-alex-perrier largedatawithscikit-learn-bostonmeetupalexperrier-bewitchedbymachinelearning-160328213501
A presentation of adaptive classification and regression algorithms available in scikit-learn with a Focus on Stochastic Gradient Descent and KNN. Performance examples on 2 Large datasets are presented for SGD, Multinomial Naive Bayes, Perceptron and Passive Aggressive Algorithms.]]>
A presentation of adaptive classification and regression algorithms available in scikit-learn with a Focus on Stochastic Gradient Descent and KNN. Performance examples on 2 Large datasets are presented for SGD, Multinomial Naive Bayes, Perceptron and Passive Aggressive Algorithms.]]> Mon, 28 Mar 2016 21:35:01 GMT /alexip/large-data-with-scikitlearn-boston-data-mining-meetup-alex-perrier alexip@slideshare.net(alexip) Large data with Scikit-learn - Boston Data Mining Meetup - Alex Perrier alexip A presentation of adaptive classification and regression algorithms available in scikit-learn with a Focus on Stochastic Gradient Descent and KNN. Performance examples on 2 Large datasets are presented for SGD, Multinomial Naive Bayes, Perceptron and Passive Aggressive Algorithms. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/largedatawithscikit-learn-bostonmeetupalexperrier-bewitchedbymachinelearning-160328213501-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A presentation of adaptive classification and regression algorithms available in scikit-learn with a Focus on Stochastic Gradient Descent and KNN. Performance examples on 2 Large datasets are presented for SGD, Multinomial Naive Bayes, Perceptron and Passive Aggressive Algorithms.
Large data with Scikit-learn - Boston Data Mining Meetup - Alex Perrier from Alexis Perrier
]]> 1654 4 https://cdn.slidesharecdn.com/ss_thumbnails/largedatawithscikit-learn-bostonmeetupalexperrier-bewitchedbymachinelearning-160328213501-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-alexip-48x48.jpg?cb=1615294923 Lead Data Scientist focused on Natural Language Processing and Predictive Modeling, a background in stochastic processes and signal processing and extensive experience in agile software development. I recently authored a book on AWS Machine Learning with Packt Pub. I am a creative start-up co-founder with clear communication skills, project management and business development experience. Team lead and team builder. You can follow me on twitter @alexip and read my blog at alexisperrier.com alexisperrier.com https://cdn.slidesharecdn.com/ss_thumbnails/alexisperrierglobalbigdatanycml171024-171023151937-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/aws-machine-learning-big-data-nyc/81106818 AWS Machine Learning B... https://cdn.slidesharecdn.com/ss_thumbnails/upem-topicmodeling-170604121319-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/cours-de-topic-modeling/76630004 Cours de topic modeling https://cdn.slidesharecdn.com/ss_thumbnails/parismeetupslidestopicmodelingoftwitterfollowersalexperrier-bewitchedbymachinelearning-160328213711-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/topic-modeling-of-twitter-followers-paris-machine-learning-meetup-alex-perrier/60133252 Topic modeling of Twit...