Pune JS Meet -Talentica Chapter: Git Internals

This meetup aims to help you visualize what Git is, what exactly happens inside the local repository when you run different commands and how to avoid and recover from some non-trivial situations.

Place:

Talentica software Pvt.Ltd.office No. 501 Amar Megaplex, Above D-Mart, Baner Pune, 411045

Talentica’s engineers to share their ML research at IEEE ICMLA2018

Machine Learning engineers from Talentica Software will be presenting their work on Fingerprinting Latent Structures at the 17th IEEE ICMLA 2018, Orlando, FL.

Summary of the Paper

One of the components of a Question-Answering (QA) system is an algorithm that can understand the articulation style of questions. Such an algorithm, if based on Machine Learning (ML), would require a large number of example questions for training. However, if one observes closely, the way we articulate questions depends on the answer we expect, which in turn is in the context of an underlying knowledge base. Grammar also plays an important role. This means we need examples of questions with different articulation styles to train the ML system.

Take this question: How many balls make an over? What is the knowledge-base for this question and what does the answer look like in the context of the knowledge-base? Those of you who are familiar with Cricket know that the answer is 6 valid balls where a ball is a type of action performed by the bowler. Now, let us look at the different ways to articulate the cricket related question: In an over, how many balls are there? The bowler can bowl, how many balls in an over? How many valid balls make an over? Do you know how many balls make an over in the game of cricket? etc.. etc.. Note how the articulation style is changing but the expected answer is still the same.

To train an ML system for Question-Answering one would need a data set with all possible questions for a particular answer, and all possible questions for all possible answers. This would lead to a humongous task of data collection. The alternative is to use a data set with different articulation styles and then let the machine learn the latent structure of articulation for each style. Based on the detection of the articulation style, the corresponding answer generation system can be triggered. This alternative approach would help us build a QA system that is accurate for a few types of articulations. As and when we improve the complexity of the answer generation system, we can support questions with more complex articulation. Until then, the system can choose to ignore complex questions. A fingerprinting system can be implemented to learn these articulation styles.

In this paper, the authors formulate the problem of understanding question articulation as an objective-driven optimization problem where examples of complementary objectives are not available. They show how the optimization problem can be solved and implemented using auto-encoders for fingerprinting. They also present k-fingerprints, an algorithm that refines clusters of questions such that the ability to separate articulation styles becomes more accurate. To know the technical details of the approach take a look at this pre-print. If one is interested in extending the technique to images, get some clues from this Slideshare.

 

Talentica will be attending Money20/20

Talentica will be present at Money20/20 USA to be held at The Venetian in Las Vegas on October 21-24, 2018.

About the Event:

The 2018 event will focus on the mission of creating a simpler, fairer, faster and more inclusive financial system for individuals, businesses, and society as a whole.

Talentica Exhibiting at TechCrunch Disrupt SF

Talentica is happy to be one of the key exhibitors at TechCrunch Disrupt yet again.

About the Event:

TechCrunch Disrupt is the world’s biggest and most impactful tech startup conference, and this year, we’re upping the stakes even more. Taking place at Moscone West, Disrupt SF will feature the biggest names in tech, from Reid Hoffman to Kirsten Green to Dara Khosrowshahi.

C2M – Mobile App Networking

This is the 5th meetup of the C2M (or Concept 2 Market) series, please see below for recordings of the previous meetups. It is not mandatory to watch previous meetups recordings, but it will give you a context.

Place:

Talentica software Pvt.Ltd.office No. 501 Amar Megaplex, Above D-Mart, Baner Pune, 411045

C2M – Mobile App Design

This is the 4th meetup of the C2M (or Concept 2 Market) series, please see below for recordings of the previous meetups of this series. It is not mandatory to watch previous meetups recordings, but it will give you a context.

Place:

Talentica software Pvt.Ltd.office No. 501 Amar Megaplex, Above D-Mart,Baner Pune, 411045

C2M – Mobile App Architecture

This is the 3rd meetup of the C2M series, please see below for recordings of the previous meetups of this series. It is not mandatory to watch previous meetups recordings, but it will give you a context.

Place:

Talentica software Pvt.Ltd.office No. 501 Amar Megaplex, Above D-Mart,Baner Pune, 411045

Continuous Integration and Deployment with AWS Code Services

Talentica software hosted a meetup on 3rd February, 2018. Participants dived deep into CI/CD pipeline use cases and its automation know-how. The agenda for the meetup was:

  • Automate Software build and release process using AWS services
  • Setup AWS CodeCommit for source control
  • Build and test code with AWS CodeBuild
  • Automate CI/CD process with AWS CodePipeline
  • Live Demo
  • Discussion
  • Q&A session
Place:

Talentica software Pvt.Ltd.office No. 501 Amar Megaplex, Above D-Mart,Baner Pune, 411045

New England Venture Summit, 2017, Boston Randolph, MA

Building on its premise of technology partners for  startups,, Talentica Software is proud to be associated with the New England Venture Summit, 2017, as one of the Sponsors. The summit is the brainchild of the Young Startup Ventures and the 12th annual edition takes place on the 6 December, 2017 at the Lombardo’s Conference Center, Boston Randolph, MA

Place:

Lombardo’s Conference Center, Boston Randolph, MA