Education content providers for data science and mathematic needed.

We are hiring education content providers for data science and mathematic.

Requirements:
1. Smart and get job done.
2. Experience in Python and Jupiter Notebook.
3. Excellent English writing skill.
4. The education content must be completed in 6 months.
5. A computer science degree.
6. Experience with Machine Learning technique.

Syllabus: http://intellij.my/PyMathCamp_syllabus.pdf

Please do not hesitate to reach nurdin@intellij.my for more inquiries.

Data science.

Data science.

Grouping on Github Event using k-means clustering

In this section we will use k-means clustering to group developers based on how similar their situation has been event-by-event. That is, we will cluster the data based in the 26 variables that we have. Continue previously from http://intellij.my/2016/03/30/dimensionality-reduction-on-github-event-using-pca-approach/ .

And now we are ready to plot, using the cluster column as color.

cluster plot chart

cluster plot chart

 

Reinvent Blockchain with Artificial Intelligence

Austin Flow Map 1 12-15-08

Blockchain is the future of finance. It is the future of how all transactions is going to work. We are talking about money, business and the world. Blockchain decentralizes all transactions via nodes, which are participated by market participants such as peoples, businesses, banks and securities firms. It is state-of-the-art technology. Thus, the blockchain thinking is required now in order to create efficient transactions for enlarging future.

Bittersweet of Blockchain.

Blockchain will be used to create smarter, more efficient systems for all supply chains, gaming, multi-media rights management, car rental, real estates sell & purchase, Government proof of identity and insurance record management.

Openness, speed, security, privacy, reliability, accountability and transparency will be the key values running in blockchain thinking. The only bitter thing about blockchain is middlemen/intermediaries will be cut out.

Auto-compliance.

We believe that AI is making world a better place. We are interested about AI role in Blockchain.

The technology is powered by second generation, as the first one has brought us to Internet of information era. The second generation is demanding compliance in their businesses, which has open new innovation door to transform all human affairs, wiser.

You should care because you would wanted to know where is this meat came from. Or for artist, you wanted to know who is currently have your trademarked/IP properties. For donors, you can know where you donations goes to. For Muslim, you can know where and how your zakaat is managed.

Now, you know the capabilities of this revolution. Blockchain is indeed an intense creation.

Permissionless & Permissioned Blockchain.

Blockchain is originally permissionless, publicly shared and decentralized. Meaning, it is detached from the central monetary system. Historically, Bitcoin is one of the famous and the most ideal cryptocurrency for technology fundamentalists. But not economists. Security firms claimed that participants that are involved in permissionless Blockchain is danger to the society that the firms faced difficult time to track suspicious activity.

Second, the ledger is shared to act as a source of truth for businesses in the blockchain. This means, shared ledger can records all transactions across the business network among participants and copies of the records are exact and replicable.

Today, permissioned and private Blockchain are existing. Permissioned means participants can only see sufficient documents that requires consensus/agreement/permission. They need to be validated from involved ends to reach consensus. This is to lower the risk of faulty transactions since interference can be occured across many places at the exact same time.

Blockchain network will be not just public ledger, but also concern about private parties in which only authorized parties are allowed to join in the transactions. Records can be protected with a digital signature and to seal the record, the permissioned blockchain will generate a private and public key. Therefore, participants can only see what they are allowed to see. Versioning history of unique IDs for customer, invoice and reference numbers will be appear clear and transparent in all transactions which are unchangeable and final.

IntelliJ’s quest in Blockchain.

Despite all these fancies about Blockchain, we like to extend its capability argumentatively.

Efficiency, trust-ability and independence are the keys of a mining operation so to record transactions.

We are interested in this quest:

How to make the operation to think independently and shared mutual way of thinking in all networks as creatively and spontaneously as an ingenuine human?

Conclusion.

Finally, we are absolutely aware that blockchain will create winners and losers. Although so, we cannot afford dislocation and insecurity in our money management.

Centralized is thought as suitable for building-fintech-products thinking, whilst decentralized is more free-ier, allowing re-innovation in the whole operation. Both ways are responsible to generate prosperity to the country.

In case you are interested too in innovating blockchain technology, we should spend more time in its thinking within compliant philosophy together because the disruption is real and is indeed coming into the way.

Imagine about empowering blockchain in all IoT network. For that, time will be the ultimate unit of measurement.

Fin.

Transformation is not about improving, it is about re-thinking. -Malcolm Gladwell

How to think like a computer scientist?

Alan Turing as a Computer Scientist

Alan Turing as a Computer Scientist

What is science? What is computer science anyway? Computer science is the study of computers. It is an art of science that representing and processing information. How about definition of computer scientist? Each person has their own perspective and way of looking at things about the definition itself. It is more related to concept of theoretical, engineering and solution provided on specific domain of computer science. Most of the time, computer scientist field conquered by male gender instead of female because of the two reasons. First, is there are no fair and equality treat to women compare to male and increasing disturbing possibility where women can be a computer scientist that discouraged them to participate. Second is related to demographics where male often entering colleagues and the jobs opportunity are more towards to male compare to female. How to think like a computer scientist? Computer scientist not only think solely about technical perspective but it’s beyond than that. In this case study, we will discuss more details about 3 views how to think like a computer scientist.

First view is computer scientist must have interacted faith when dealing with science. Science without philosophy is blind but philosophy without science is emptiness. So religion perspective is very important when we want to conclude any hypothesis before it been made. Even new great discoveries have found by the computer scientists without religion and philosophy involvement, it will become blind and strayed because no proper aim, objectives and goals. But experiment or observation on the name of science without religion and philosophy are useless and emptiness because unknowing purpose of creation.

Second view is a computer scientist must always present solutions to problems, to prove some math theorems, to make precise analyzes of computational tasks, to propose general theories, or to organize bodies of knowledge. Compare to mathematicians who do algebra think different from mathematicians who do geometry but both kinds of mathematicians think different from computer scientists who work on useful algorithms that computer can perform. Computer scientist also need to think about the hardware and software. There are a lot of computer problems can be solved with proper techniques as mention before this, one of it is to create an effective algorithm because we believe computer or “machine” far more powerful and capable of solving real world problems which humans cannot do.

Third view is computer scientist need to work in three distinguishable areas which are design of hardware components and especially total systems, design of basic languages and software broadly useful in applications, including monitors, compilers, time-sharing systems and methodology of problem solving with computers. Second view is more similar to third view but it is more emphasize computer scientist areas. One example related to hardware components, currently computer scientist successfully found a way how to optimize the hardware memory and boost up computation capability according to Moore’s Law. They try to emulate computer like human brain so it can process more complex algorithm and at the same time try to copycat human brain to be an artificial computer brain.

References

  1. Knuth, D. (1999). Things a Computer Scientist Rarely Talks About. 1-26. Retrieved October 6, 1999.
  2. FORSYTHE, G. E. (1967). WHAT TO DO TILL THE COMPUTER SCIENTIST COMES. 1-15. Retrieved September 21, 1967.
  3. Pearl, A., Pollack, M. E., Riskin, E., Thomas, B., Wolf, E., & Wu, A. (1990). Ecoming a Computer Scientist. 1-9. Retrieved 1990.