Jessica Mah makes cover of Inc.

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Posted by Lawrence Sinclair on 18 Aug 2015 at 05:56

Indinero has been a client of ours for several years. I'm proud to note that their CEO, Jessica Mah, has made the cover of Inc Magazine. 

Jessica on the cover.

 

Jessica Mah and her co-founder, Andy Su, with two of their East Agile engineers in the East Agile office in Vietnam.

 

East Agile client ToutApp Raises $15 million

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Posted by Lawrence Sinclair on 03 Mar 2015 at 15:23

In 2011,Toutapp hired East Agile to help with software development. Like many of our clients, they have done well. In 2013, they raised $920,000 from Dave McClure's 500startups.  Today, an announcement went out that they have raised a Series B let by Andreessen Horowitz for another $15 million dollars. See http://techcrunch.com/2015/03/03/toutapp-series-b/

Client inDinero raised $7 million in new funding

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Posted by Lawrence Sinclair on 19 Feb 2015 at 16:49

On February 18th, 2015, inDinero, our longtime client raised another $7 million in new funding as reported in Techcrunch. So far they have raised about $10 milllion. At one point things got tough and they had to lay off all of their staff. But we've supported them through thick and thin over the years.

See http://techcrunch.com/2015/02/18/indinero-pivot-funding

EAST AGILE HOLIDAYS SAN FRANCISCO OFFICE 2015

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Posted by Anonymous on 02 Dec 2014 at 04:13

Our office in San Francisco has limited staff during the following days in 2015.

1.     New Year’s Day
Thursday January 1st.

2.     Birthday of Martin Luther King, Jr.
Monday January 19th.

3.      Washington's Birthday
Monday February 16th.

4.      Memorial Day 
Monday May 25th.

5.      Independence Day
Friday July 3rd.

6.       Labor Day
Monday September 7th.

7.       Columbus Day
Monday October 12th.

8.       Veterans Day
Wednesday November 11th.

9.       Thanksgiving Day
Thursday November 26th.

10....

EAST AGILE HOLIDAYS VIETNAM 2015

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Posted by Anonymous on 02 Dec 2014 at 04:12

Hours of Operations

With the exception of these holidays, East Agile Vietnam’s core operating hours are 8am to 5pm, Monday through Friday (ICT, Indochina Time, UTC+7).

- In Pacific Time (PST, UTC-8), our working hours are 5pm to 2am. During Daylight Saving Time, our hours are from 6pm to 3am PDT.

- In Eastern Time (EST, UTC-5), our working hours are 8pm to 5amDuring Daylight Saving Time, our hours are from 9pm to 6am EDT.

- U.S. Daylight Saving Time begins on Sunday, March 8, 2015 and ends on Sunday, November 1, 2015. Vietnam does not follow Daylight Saving Time.

See http://bit.ly/tq3Ijs to translate to your time zone.

Holidays

Our office in Vietnam has limited staff during the following holidays in 2015.

1.    New...

EAST AGILE HOLIDAYS SAN FRANCISCO OFFICE 2014

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Posted by Anonymous on 29 Nov 2013 at 10:52

Our office in San Francisco has limited staff during the following days in 2014

1.     New Year’s Day
Wednesday January 1st.

2.     Birthday of Martin Luther King, Jr.
Monday January 20th.

3.      Washington's Birthday
Monday February 17th.

4.      Memorial Day 
Monday May 26th.

5.      Independence Day
Friday July 4th.

6.       Labor Day
Monday September 1st.

7.       Columbus Day
Monday October 13th.

8.       Veterans Day
Tuesday November 11th.

9.       Thanksgiving Day
Thursday November 27th.

10.   ...

EAST AGILE HOLIDAYS VIETNAM 2014

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Posted by Anonymous on 29 Nov 2013 at 10:41

Hours of Operations

With the exception of these holidays, East Agile Vietnam’s core operating hours are 9am to 6pm, Monday through Friday (ICT, Indochina Time, UTC+7).

See http://bit.ly/tq3Ijs to translate to your time zone.

Holidays

Our office in Vietnam has limited staff during the following holidays in 2014.

1.    New Year’s Day (Tết Dương Lịch)
Wednesday January 1st.

2.    Tet (Tết Nguyên Đán) [Friday, January 31st]
Thursday January 30th,
Friday January 31st,
Monday February 3rd,
Tuesday February 4th,
Wednesday February 5th.

3.     Hung Kings’ Commemoration (Giỗ Tổ Hùng Vương)
Wednesday April 9th.

4.     Reunification Day (...

iOS testing frameworks and Appurify

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Posted by Anonymous on 23 Sep 2013 at 17:17

Recently, I had a chance to experience some parts in the world of iOS testing. This post is my opinion on various testing frameworks, and the promising, powerful testing and debugging platform - Appurify.
 
- KIF: tests are written in Objective-C and divided into three "levels": Test Controller, Test Scenarios and Test Steps. Nice structure -- but we will have to create more files. KIF aims to directly manipulate the app and attempts to imitate actual user input. The limitation for that is KIF can not handle system views such as in-app purchase popups, which are outside of the app's scope.
 
- Subliminal: tests are based on UIAutomation while being written entirely in Objective-C. It was created to solve the problems KIF left - handling system scope views....

Text Mining in Apache Mahout

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Posted by Anonymous on 29 Aug 2013 at 18:51

Lately we've been working on text mining using clustering techniques to group together similar documents. Apache Mahout has proven an excellent tool for this. Mahout is an open-source library that implements scalable machine learning algorithms. It is very fast and has excellent integration with other popular open-source Apache libraries, such as hadoop and lucene. One of mahout's core capabilities is clustering. To perform text mining, simply take a bunch of text documents, represent each document as a feature vector that says which words the document contains, and apply a clustering algorithm. A possible application is grouping blogs into different groups that can be targeted for ads.
 
Here's the basic workflow in mahout:
 
1. Start with a dataset, i.e. a...

Adventures in Machine Learning

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Posted by Anonymous on 26 Jul 2013 at 23:07

Lately I have been thinking about how to recommend movies to movie watchers, purchases to shoppers, artists to music lovers. In general, if you have a bunch of items and a bunch of users, how do you figure out which items to recommend to which users?

There are many solutions to this problem. One extreme solution is to ask a movie connoisseur to learn the movie watcher's tastes, habits, lifestyle, and more. Then the movie connoisseur carefully picks out a few movies he thinks the movie watcher would enjoy. While this solution can produce incredibly personalized results, it is very time-consuming and does not scale. The solution on the opposite end of the spectrum is collaborative filtering. In collaborative filtering, you take all the existing data on which movie watchers like...