Tag: Classification

Feed: Featured Blog Posts - Data Science Central. Author: William Vorhies. Summary:  Got a good AUC on your hold out data?  Think that proves that it’s safe to put the model into production.  This article shows you some of the pitfalls in this new era of black box Deep Learning Neural Nets and a method for identifying potentially devastating errors.                         Image source: XKCD Recently we’ve been reading that the increased adoption of Deep Learning (DL) image, text, and voice processing tools has been driven by the fact that major ... Read More

Feed: Planet big data Author: David Smith by Fang Zhou, Data Scientist at Microsoft and Wee Hyong Tok, Senior Data Scientist Manager at Microsoft In today’s fast-paced world, mobile phone customers have many choices and can easily switch between service providers. Improving customer attrition rates and enhancing a customer’s experience are valuable ways to reduce customer acquisition costs and maintain a high-quality service. Many industries, including mobile phone service providers, use churn models to predict which customers are most likely to leave, and to understand which factors cause customers to stop using their service. In this blog post, we sketch a solution to ... Read More

Feed: Google Cloud Big Data and Machine Learning Blog. Author: Google Cloud Big Data and Machine Learning Blog Team. Innovation in data processing and machine learning technology Wednesday, August 17, 2016 Posted by Sara Robinson, Developer Advocate You may know the Cloud Vision API for its face, object, and landmark detection, but you might not know that the Vision API can also detect inappropriate content in images using the same machine learning models that power Google SafeSearch. Since we announced the Google Cloud Vision API GA in April, we’ve seen over 100 million requests for SafeSearch detection. Any application with ... Read More

Feed: Google Cloud Big Data and Machine Learning Blog. Author: Google Cloud Big Data and Machine Learning Blog Team. Innovation in data processing and machine learning technology Tuesday, July 26, 2016 Posted by Kaz Sato, Staff Developer Advocate You may have heard the buzz about neural networks and deep learning, and want to learn more. But when you learn about the technology from a textbook, many people find themselves overwhelmed by mathematical models and formulas. I certainly was. For people like me, there's an awesome tool to help you grasp the idea of neural networks without any hard math: TensorFlow ... Read More

Feed: Google Cloud Big Data and Machine Learning Blog. Author: Google Cloud Big Data and Machine Learning Blog Team. Innovation in data processing and machine learning technology Monday, May 23, 2016 Posted by Lak Lakshmanan, Big Data & Machine Learning Professional Services, Google Cloud Platform Demand forecasting is something that every business does. If you're a restaurant owner, you need to forecast how many diners you'll have tomorrow and what foods they'll order so that you know what ingredients to shop for and how many cooks to have in your kitchen. If you sell shirts, you need to predict in ... Read More

Feed: SQL Server Blog. Author: SQL Server Team. This post was authored by Rimma Nehme, Technical Assistant, Data Group. Since its birth in 2009, and the time it was open sourced in 2010, Apache Spark has grown to become one of the largest open source communities in big data with over 400 organizations from 100 companies contributing to it. Spark stands out for its ability to process large volumes of data 100x faster, because data is persisted in-memory. Azure cloud makes Apache Spark incredibly easy and cost effective to deploy with no hardware to buy, no software to configure, with ... Read More

Feed: AWS Government, Education, & Nonprofits Blog. Author: publicsector. Last week we highlighted the 2016 City on a Cloud Innovation Challenge Award Winners. We showcased the five winners for the Best Practices Award and the five winners for the Dream Big Award. In addition, Appriss, GRIDSMART, OpenDataSoft, SmartProcure, and Utility, Inc. were this year’s Partners in Innovation Award recipients, recognizing applications that solve local and regional government challenges.Check out each of the partner winners below: Appriss – Prior to the introduction of VINE, an automated, reliable method for victims of crime to be notified of offender incarceration status did not ... Read More

Feed: AWS Big Data Blog. Ujjwal Ratan is a Solutions Architect with Amazon Web Services The Hospital Readmission Reduction Program (HRRP) was included as part of the Affordable Care Act to improve quality of care and lower healthcare spending. A patient visit to a hospital may be constituted as a readmission if the patient in question is admitted to a hospital within 30 days after being discharged from an earlier hospital stay. This should be easy to measure right? Wrong. Unfortunately, it gets more complicated than this. Not all readmissions can be prevented, as some of them are ... Read More

Feed: AWS Big Data Blog. Manjeet Chayel is a Solutions Architect with AWS Streaming data is everywhere. This includes clickstream data, data from sensors, data emitted from billions of IoT devices, and more. Not surprisingly, data scientists want to analyze and explore these data streams in real time. This post shows you how you can use Spark Streaming to process data coming from Amazon Kinesis streams, build some graphs using Zeppelin, and then store the Zeppelin notebook in Amazon S3. Apache Zeppelin is an open source GUI which creates interactive and collaborative notebooks for data exploration using Spark ... Read More

Feed: AWS Big Data Blog. Bruno Faria is a Big Data Support Engineer for Amazon Web Services Many data scientists choose Python when developing on Spark. With last month’s Amazon EMR release 4.6, we’ve made it even easier to use Python: Python 3.4 is installed on your EMR cluster by default. You’ll still find Python 2.6 and 2.7 on your cluster, but the inclusion of 3.4 means you no longer have to configure custom bootstrap actions to install Python 3 on EMR. An EMR 4.6 cluster running Spark 1.6.1 will still use Python 2.7 as the default interpreter ... Read More