Waitwhile is built with AngularJS and relies on Firebase for storage, authentication, hosting and even communication with email and SMS. This post will explore how to juice up your Firebase app with realtime text notifications using Zapier and Twilio.
Tag Archives: SMS
In this post, we are going to build a simplified GroupMe clone using Meteor, MongoDB, and Twilio. The app will serve as an SMS group messenger that will let us create groups of phone numbers and blast a text message to every member of that group. We will also expand its functionality to allow groups and individual numbers to be toggled on or off depending on who we want to receive a particular text.
If at any point you are receiving errors and feel lost, or you just want to run this application without building it, you can obtain the finished source code here.
Otherwise, prepare to explore the Meteor universe.
A very useful feature in Android is the
SmsManager API which you can use to send an SMS from inside your own Application. Actually there are two way you can send an SMS from your Application:
- Using the build in SMS activity of Android API
SmsManagerAPI, you can customize your own Activity the way you want and use it in any manner you choose, so it’s much more flexible. So, in this tutorial we are going to examine both ways.
For this tutorial, we will use the following tools in a Windows 64-bit platform:
- JDK 1.7
- Eclipse 4.2 Juno
- Android SKD 4.2
The field of natural language processing and the many topics encompassed within it (summarization, full-text search, sentiment analysis, content categorization, etc.) is one of fastest growing, most complex and most highly demanded knowledge sets in the software industry today.
From spell checking in your SMS client to programmatically evaluating what your Twitter followers think of you, there is no shortage of real-world text processing and linguistic analysis problems all around us waiting to be solved. As Rubyists and software engineers, its important for us to know what tools related to NLP are available to us and how we can make use of them most effectively.
While there are a number of really great open-source libraries for natural language processing in Ruby and many great strides have been made in recent years, there’s still often a need to leverage tools and libraries externally from the Ruby ecosystem. Some of the best open-source NLP frameworks available rely very heavily on contributions from the academic world where Ruby as a language doesn’t have the same presence as other languages like Python or Java.
In this talk, I’ll provide a beginner friendly introduction to NLP in general and I’ll give a quick overview of the tools and related projects that are currently available in the Ruby community. In addition, using real-world examples I’ll demonstrate how to painlessly leverage high performance, mature and well-established NLP libraries directly from your Ruby application using JRuby and JDK 7.