• Recommendation Systems

    TengerData Services 2017
  • Artificial Neural Networks

    TengerData Services 2017
  • Deep Learning

    TengerData Services 2017
  • Integrated AI Systems

    TengerData Services 2017
  • Collaborative Filtering

    TengerData Services 2017

Deep Lerning for Recommenders

TengerData introduces Conversion++ Updated: 2017-8-20

What is a Recommendation System?

A recommendations system is an information filtering technology. Recommenders are commonly used on e-commerce and VOD platforms that use collaborative filtering.

Big companies like Amazon, eBay, YouTube, Netflix and many others are using recommendation systems.


Who else should use recommenders?

Other than VOD, e-commerce and online shopping networks, there are many other online platforms using content and product recommendation system to increase their sales.

The main purpose of a recommender is to present information on items and products that are likely to be of interest to the user.


Is it worth it to build recommenders?

All the online giants must think it’s worth it, because they are using deep learning recommendation engines. They all understand that if they don’t use powerful recommendation systems they will all be bankrupted very quickly.

Do I need a recommender?

Acting solely on a hunch is no longer necessary, nor is it a good idea in today’s business environment. Using our cutting edge deep learning solutions, you don’t have to rely on chance anymore.

Should I use a Deep Learning recommender?

YouTube uses Deep Neural Networks. The company explains: “Deep Learning recently had an immense impact on the YouTube video recommendations system.”



Do you know exactly what the visitors are doing on your site?

Our Deep Learning models will learn and recognize your visitors behavior pattern on your website.

Do you know what your users like or dislike?

Our algorithms will predict, with a high level of accuracy, what each visitor likes and dislikes on your website.



Does your system trigger a targeted Call to Action?

Our model will trigger a highly targeted “Call to Action”, based on real-time analytics of user behavior patterns, using integrated Deep Neural Networks.

Why TengerData?

TengerData has a sustainable competitive advantage, because we are working with highly skilled, English & Chinese speaking deep learning specialists in Taiwan.

Our organizational structure and creative environment enables us to develop a recommendation system for a fraction of the costs our competitors charge in the US or Europe.

Getting started: 3 simple steps.

Recommenders are highly complex systems. But, the process to get started is simple. Even a journey of a thousand miles begins with one step.

Step #1: Consulting Services.

Our role as a consultant is generally to provide insights into the recommendation system development process.



Step #2: Exploring the possibilities.

We offer a comprehensive evaluation of the options, based on your unique business situation and the technical specifications of your existing platform.



Step #3: Making an educated decision.

When the options are well understood, we will help you make an educated decision whether or not you are ready for the recommender.



Building the Recommendation System

If your decision is to build a recommender, we will take the optimal approach to develop a powerful system for you, based on your specific needs.

Free Consultation

  • Recommendation Systems

    TengerData Services 2017
  • Artificial Neural Networks

    TengerData Services 2017
  • Deep Learning

    TengerData Services 2017
  • Integrated AI Systems

    TengerData Services 2017
  • Collaborative Filtering

    TengerData Services 2017