Início PAPIs 2017 no InfoQ Brasil
Apresentações
Feed RSS-
A TenserFlow recommender system for news
Attending this presentation you're going to follow a detailed overview of how R&D team of Hearst's TV division is putting together Google BigQuery, Kubernetes cluster and Tensorflow to build a hy(...)
/presentations/a-tenserflow-recommender-system-for-news/pt/mediumimage/Fabricio-Vargas_270-1510576053285.jpg)
-
Improving customer value estimation by predicting conversion
The objective of this presentation is to describe the challenges of modeling a customer conversion predictor using real leads data observed on different levels of the conversion funnel. It will i(...)
/presentations/improving-customer-value-estimation-by-predicting-conversion/pt/mediumimage/Allan-Dieguez_270-1510007425882.jpg)
-
Building Machine Learning Service in your business
When making machine learning applications in Uber, we identified a sequence of common practices and painful procedures, and thus built a machine learning platform as a service. We here present th(...)
/presentations/building-machine-learning-service-in-your-business/pt/mediumimage/Eric-Chen_270-1508807987521.jpg)
-
Discovering hidden treasures in yout data with graph analytics
Companies data are most from DB and mined using traditional data mining approach. However, model relational data as a graph can reveal useful insights and discovery relation among data that is ig(...)
/presentations/discovering-hidden-treasures-in-yout-data-with-graph-analytics/pt/mediumimage/Ana-Appel_270-1508154267187.jpg)
-
Solving a business problem in 2 weeks using machine learning
Machine Learning techniques are amazing to solve a bunch of complex business problems efficiently and also in a very fast manner with all of the available tools that we have nowadays. We will sho(...)
/presentations/solving-a-business-problem-in-2-weeks-using-machine-learning/pt/mediumimage/Lucas-Pedro_270-1507899272586.jpg)
-
Optimizing battery life with data mining and ML
Battery life is critical for smart devices, but optimizing it requires cooperation from the entire software ecosystem. Our project aims to streamline energy-related bug processing in devices of(...)
/presentations/optimizing-battery-life-with-data-mining-and-ml/pt/mediumimage/Ramon-Oliveira_270-1506991176503.jpg)
-
Improving a recommendation engine with transfer learning
In this talk, we will describe how we improved an online vacation retailer recommender system by using the information in images. We’ll explain how to leverage open data and pre-trained deep lear(...)
/presentations/improving-a-recommendation-engine-with-transfer-learning/pt/mediumimage/Pierre-Gutierrez_270.jpg)
-
Getting value from data science in the Telco business: the journey of Vivo Data Labs
In this presentation, we will go through the main challenges faced by the data scientists team since its creation and how we could leverage disruptive changes in our business process, technology(...)
/presentations/getting-value-from-data-science-in-the-telco-business/pt/mediumimage/Paula-Fadul_270.jpg)
-
Shortening the time from analysis to deployment with ML-as-a-Service
This presentation shows one architecture design using RESTful resources, document oriented databases and pre-trained pipelines to achieve real-time predictions of time series with high availabili(...)
/presentations/shortening-the-time-from-analysis-to-deployment-with-ml-as-a-service/pt/mediumimage/Luiz-Gabriel_270.jpg)
-
Building ML application locally with Spark
An introduction about a powerful machine learning library (MLlib) along with an overview of Spark, describing how to launch applications within a cluster. A demo will show how to simulate a Spark(...)
/presentations/building-ml-application-locally-with-spark/pt/mediumimage/Joel-Pinho_270.jpg)
-
Practical Machine Learning Models to prevent Revenue Loss
We offer a demonstration of machine learning (ML) to create an intelligent application based on distributed system data. We'll show ML techniques in the development of a data analysis application(...)
/presentations/practical-machine-learnning-models-to-prevent-revenue-loss/pt/mediumimage/Flavio-Eiti_270.jpg)
-
Deep Learning for sentiment analysis
Convolutional Neural Networks (CNNs) are already proven to be the state of art technique for image classification projects. However, some recent research found that it can be also used for some t(...)
/presentations/deep-learning-for-sentiment-analysis/pt/mediumimage/Andre-Barbosa_270.jpg)