Houston! We have Apps!
It’s that time of year again, and we are here to help. If you are participating in this years NASA Space Apps Challenge, below you will find the resources you need to do cool stuff like, Machine Learning, Facial Recognition, emotion tracking and more.
How can we help?
But first things first, to get started, you will need to grab yourself some free Microsoft Cloud to do your computations, and Microsoft Azure has you covered.
Need to connect with the Microsoft Space Apps Team for technical mentoring? Just email spaceapps@Microsoft.com
Getting Connected – Setting up your Azure Pass
You should have received and Azure Pass from your organizer, all you need to do is take that card and head over to http://sogeek.us/getazurepass for step by step instructions on how to get set up.
Getting Started Tutorials
Project Oxford allows developers to create smarter apps, which can do things like recognize faces and interpret natural language even if the app developers are not experts in those fields.
- Visual tools: This service can analyze visual content to look for things like inappropriate content or a dominant color scheme. It also can detect and understand text in photos, such as a team name, and can sort photos by content, such as pictures of beaches, animals or food. Finally, it can automatically edit photos down to a recognizable and useful thumbnail for easy scanning.
- Computer Vision API – https://www.projectoxford.ai/vision
- Face recognition: This technology automatically recognizes faces in photos, groups faces that look alike and verifies whether two faces are the same. It can be used for things like easily recognizing which users are in certain photos and allowing a user to log in using face authentication. It’s the same technology that is behind this fun new website that guesses how old a person looks based on a photograph.
- Face Recognition (detection, verification, emotion recognition) https://www.projectoxford.ai/demo
- Speech processing: This technology can recognize speech and translate it into text, and vice versa. A developer might use it for hands-free tools such as the ability to dictate text or to have an automated voice read out instructions or other necessary functions
- Speech to Text https://www.projectoxford.ai/demo/speech#recognition
- Text to Speech – https://www.projectoxford.ai/demo/speech#text2speech
- Speaker Identification https://www.projectoxford.ai/demo/speech#recognition
A fully managed cloud service that enables you to easily build, deploy, and share predictive analytics solutions. Azure Machine Learning means business. You can deploy your model into production as a web service in minutes—a web service that can be called from any device, anywhere and that can use any data source
- AzureML Playground https://studio.azureml.net/?selectAccess=true&o=1 (without Azure Pass)
(with azure pass will find in portal.azure.com )
- Machine Learning Videos – https://azure.microsoft.com/en-us/documentation/services/machine-learning/
- Documentation – Azure Virtual Machine Documentation: https://azure.microsoft.com/en-us/documentation/services/virtual-machines/
- Video – Building a Linux Virtual Machine: https://azure.microsoft.com/en-us/documentation/videos/building-a-linux-virtual-machine-tutorial/
- Tutorial – Create a Linux Virtual Machine: https://azure.microsoft.com/en-us/documentation/articles/virtual-machines-linux-tutorial/
- Video – Create a Virtual Machine running Windows: https://azure.microsoft.com/en-us/documentation/videos/create-a-virtual-machine-running-windows-in-the-azure-preview-portal/
- Tutorial – Create a Windows Virtual Machine : https://azure.microsoft.com/en-us/documentation/articles/virtual-machines-windows-tutorial/
- Setting up and using SQL Database on Azure http://social.technet.microsoft.com/wiki/contents/articles/2138.microsoft-azure-and-sql-database-tutorials.aspx
- Mongodb on Windows Machine – https://channel9.msdn.com/Series/MeanOnAzure/MOA-Episode-3-Mongo-in-the-Cloud-Windows-Machine
- MongoDB on Linux Machine – https://channel9.msdn.com/Series/MeanOnAzure/MEAN-on-Azure-MongoDB-in-the-Cloud-On-Linux
Internet of Things
- Intel Edison Azure IoT Starter Kit – https://azure.microsoft.com/en-us/documentation/samples/iot-hub-node-intel-edison-getstartedkit/
- Thinglabs.io – http://thinglabs.io
- Intel Edison Starter Kit Walkthrough
- Create an ASP.NET web app in Azure App Service – https://azure.microsoft.com/en-us/documentation/articles/web-sites-dotnet-get-started/
- Create a PHP web app in Azure App Service – https://azure.microsoft.com/en-us/documentation/articles/web-sites-php-mysql-deploy-use-git/
- Create a Node.js web app in Azure App Service – https://azure.microsoft.com/en-us/documentation/articles/web-sites-nodejs-develop-deploy-mac/
- Create a Java web app in Azure App Service – https://azure.microsoft.com/en-us/documentation/articles/web-sites-java-get-started/
- Create a Python web app in Azure App Service – https://azure.microsoft.com/en-us/documentation/articles/web-sites-python-ptvs-django-mysql/
Grab the Meetup Slides
- First Meetup Slides – https://onedrive.live.com/redir?resid=2068677E79E84A5E!520954&authkey=!AGFWdDhMOdllLZ4&ithint=file%2cpptx
- Second Meetup Slides – https://onedrive.live.com/redir?resid=2068677E79E84A5E!473471&authkey=!AHj69ZXQ_JQTLeY&ithint=file%2cpptx
If you are looking for some inspiration for your hack, check out the video below.