“DEEP LEARNING PROJECT” starts now. I believe it works in digital marketing and economic analysis


As the new year starts,  I would like to set up a new project of my company.  This is beneficial not only for my company, but also readers of the article because this project will provide good examples of predictive analytics and implementation of new tools as well as platforms. The new project is called “Deep Learning project” because “Deep Learning” is used as a core calculation engine in the project.  Through the project,  I would like to create “predictive analytics environment”. Let me explain the details.


1.What is the goal of the project?

There are three goals of the project.

  • Obtain knowledge and expertise of predictive analytics
  • Obtain solutions for data-driven management
  • Obtain basic knowledge of Deep Learning

As big data are available more and more, we need to know how to consume big data to get insight from them so that we can make better business decisions.  Predictive analytics is a key for data-driven management as it can make predictions “What comes next?” based on data. I hope you can obtain expertise of predictive analytics by reading my articles about the project. I believe it is good and important for us  as we are in the digital economy now and in future.


2.Why is “Deep Learning” used in the project?

Since the November last year, I tried “Deep Learning” many times to perform predictive analytics. I found that it is very accurate.  It is sometimes said that It requires too much time to solve problems. But in my case, I can solve many problems within 3 hours. I consider “Deep Learning” can solve the problems within a reasonable time. In the project I would like to develop the skills of tuning parameters in an effective manner as “Deep Learning” requires several parameters setting such as the number of hidden layers. I would like to focus on how number of layers, number of neurons,  activate functions, regularization, drop-out  can be set according to datasets. I think they are key to develop predictive models with good accuracy.  I have challenged MNIST hand-written digit classifications and our error rate has been improved to 1.9%. This is done by H2O, an awesome analytic tool, and MAC Air11 which is just a normal laptop PC.   I would like to set my cluster on AWS  in order to improve our error rate more. “Spark” is one of the candidates to set up a cluster. It is an open source.


3. What businesses can benefit from introducing “Deep Learning “?

“Deep Learning ” is very flexible. Therefore, it can be applied to many problems cross industries.  Healthcare, financial, retails, travels, food and beverage might be benefit from introducing “Deep Learning “.  Governments could benefit, too. In the project, I would like to focus these areas as follows.

  • Digital marketing
  • Economic analysis

I would like to create a database to store the data to be analyzed, first. Once it is created,  I perform predictive analytics on “Digital marketing” and “Economic analysis”.  Best practices will be shared with you to reach our goal “Obtain knowledge and expertise of predictive analytics” here.  Deep Learning is relatively new to apply both of the problems.  So I expect new insight will be obtained. For digital marketing,  I would like to focus on social media and measurement of effectiveness of digital marketing strategies.  “Natural language processing” has been developed recently at astonishing speed.  So I believe there could be a good way to analyze text data.  If you have any suggestions on predictive analytics in digital marketing,  could you let me know?  It is always welcome!


I use open source software to create an environment of predictive analytics. Therefore, it is very easy for you to create a similar environment on your system/cloud. I believe open source is a key to develop superior predictive models as everyone can participate in the project.  You do not need to pay any fee to introduce tools which are used in the project as they are open source. Ownership of the problems should be ours, rather than software vendors.  Why don’t you join us and enjoy it! If you want to receive update the project, could you sing up here?



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It is an awesome course to start learning digital marketing in 2016!

bake-1058862_640Happy new year!  This is the first article in 2016. So I would like to recommend a course to everyone who wants to learn digital marketing.

Social Media in Public Relations“is provided by Dr.Tracy Loh, Visiting Fellow Department of Communications and New Media in National University of Singapore through Coursera, one of the biggest mooc platforms.

This is good as a starting point to learn digital marketing in a theoretical manner.  I would like to introduce several interesting points from the course as they are useful and beneficial for business personnel who are interested in marketing and public relations.   These points come from week 3 ” Content Creation and Management” in the course.


1. Levels of content

There are many contents in social media so I would like to classify them effectively.   Dr.Tracy Loh provides us levels of content based on its value as follows.

Filler : information that is copied from other sources

Basic content  : original content, but relatively simple

Authority building content : Original contents that position the organization as an authority in a particular area of relevance to the organization

Pillar content : Educational content that readers use over time, save and share with others.

Flagship  : Seminal works that set the tone on an issue and which people refer back to time to come

I think this classification is very useful when we consider a portfolio of our contents  in terms of strategies of marketing and public relations. We can analyze our own content-portfolio based on levels of content. My article may be classified as “Authority building content”.  I would like to write the contents of “Flagship” in future, even though it is very difficult. Yes, you can challenge “Flagship”, too.  It should be noted that these contents should be used to reach our goals of marketing and public relation as a whole.


2. Social currency

To create viral contents, it is important that the contents have “social currency.”   Dr. Tracy Loh explains that “social currency” can be found in content that contain a level of “inner remarkability”.  For example,  when you share the new information that is not shared in your circle yet,  your social currency is increasing.  It is one of three aspects of  “social currency”. Others are explained in the course.


3. Trigger

“Trigger” is important to make content viral as daily life events can be associated with certain products.  These two examples are famous because everyone knows they are associated with daily life-events. Let us see these short videos.

Have a break, have a Kit Kat

What time is it?   It’s Tiger Time

Dr.Tracy Loh introduces this phrase  “Social currency gets people talking, but triggers keep them talking. Top of mind means tip of tongue.” (Jonah Berger, 2013)



I think we can apply these points above to our marketing strategies effectively.  Because they are theory-driven, but not so complicated.  It is easy to get some insights based on the points I referred.

I mentioned just a part of the course for the purpose of introduction. This course has many interesting topics and provides us knowledge of social media. It is free to just see the course. When you need the certification of the course,  some cost is needed to pay. I would like to recommend for you to overview the course first, and if you like it,  you can upgrade the course with the certification when it is available.  Let us enjoy this course in 2016!