Machine Learning (ML) Archives | CSE Developer Blog

Real-time time series analysis at scale for trending topics detection

Omri MendelsJanuary 2, 2019Jan 2, 201901/2/19

Managing big cities and providing citizens public services requires municipalities to have a keen understanding of what citizens care the most about. And, as the cities we live in seek more and more to become the 'smart cities' of tomorrow, this means gathering and analyzing vast amounts of data. Data gathered from social and municipal sources

Unsupervised driver safety estimation at scale, a collaboration with Pointer Telocation

Omri MendelsJuly 30, 2018Jul 30, 201807/30/18

Background Connected cars, which have the ability to collect and transfer data via cellular networks, offer us the opportunity to make road transport safer, more organized and more ecologically friendly. To push forward widespread adoption and help the technology fully enter the mainstream, manufacturers and third parties, like insurance c

Semantic Segmentation of Small Data using Keras on an Azure Deep Learning Virtual Machine

Margaret MeehanJuly 18, 2018Jul 18, 201807/18/18

Introduction As previously featured on the Developer Blog, golf performance tracking startup Arccos joined forces with Commercial Software Engineering (CSE) developers in March in hopes of unveiling new improvements to their "virtual caddie" this summer. Powered by Microsoft Azure, Arccos' virtual caddie app uses artificial intelligenc

Sequence Intent Classification Using Hierarchical Attention Networks

Olga LiakhovichMarch 6, 2018Mar 6, 201803/6/18

Introduction In this code story, we will discuss applications of Hierarchical Attention Neural Networks for sequence classification. In particular, we will use our work the domain of malware detection and classification as a sample application. Malware, or malicious software, refers to harmful computer programs such as viruses, ransomware,

Comparing Image-Classification Systems: Custom Vision Service vs. Inception

Clemens WolffDecember 5, 2017Dec 5, 201712/5/17

We recently worked with Reverb, an online marketplace for music gear. Musicians and music retailers use Reverb's platform to buy and sell items such as guitars, keyboards, effects pedals, etc. A key element that aids discovery of items listed on the Reverb site is accurate metadata. For example, the manufacturer's official name for the finish

Stock Market Predictions with Natural Language Deep Learning

Patty RyanDecember 4, 2017Dec 4, 201712/4/17

Overview We recently worked with a financial services partner to develop a model to predict the future stock market performance of public companies in categories where they invest. The goal was to use select text narrative sections from publicly available earnings release documents to predict and alert their analysts to investment opportuni

Autoscaling Deep Learning Training with Kubernetes

Rita ZhangNovember 21, 2017Nov 21, 201711/21/17

Background We recently partnered with Litbit, a San Jose-based startup, on a project to autoscale deep learning training. Litbit enables its customers to turn their "Internet of Things” into conscious personas that can learn, think, and do helpful things. In order to accomplish this goal, customers train their AI-empowered personas using

Automating Receipt Processing

CY YamJuly 5, 2017Jul 5, 201707/5/17

Claiming expenses is usually a manual process. This project aims to improve the efficiency of receipt processing by looking into ways to automate this process. << You need to include a little more context here. I understand that you don't want to name the partner, but it'd be great if you could include some context about why this is

Building an Image Classification Pipeline Using Serverless Architecture

Jason FoxJuly 1, 2017Jul 1, 201707/1/17

Background The International Committee of the Red Cross (ICRC) Trace-the-Face program uses photos to match up missing family members who have been separated due to migration and conflict. We have been working with the ICRC to update and extend Trace-the-Face to perform automatic face detection and matching using machine learning, via Micr

IoT Sports Sensor Machine Learning Helps Amateurs Up Their Game

Patty RyanJune 29, 2017Jun 29, 201706/29/17

Recently, Microsoft partnered with the Professional Ski Instructors of America and the American Association of Snowboard Instructors, (PSIA-AASI) to use wearable IoT sensors in order to develop a machine learning model of skiing skills and expertise levels. PSIA-AASI continually evaluates new technology and methods for nurturing learning ex

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