Thoughts without boundaries
All Sri Lankan industries have gone through setting up startups and growing them to great success over the years, many of them while the war was going on – we all know how difficult it was but all intelligent intellectuals took it very seriously and played their most important roles. By the time the war ended, they were ready to take our industries to next level because they never gave up while the war continued and despite the political drama and selfish international bodies who tried destroying our motherland. Let me remind you this, our generation and the generation before that, went through a difficult and a painful time period from 1983 to 2009 incidents occurred, many of us are parents today! everybody knows how hard and how painful every second we all spent that time period. It’s time, let’s get together to rebuild Sri Lanka, let’s unite let’s only worry about those who need help to recover. As entrepreneurs, Our role is to get all investments and keep moving forward, we will never take a step back developing ourselves and this one of a kind beautiful country with most beautiful souls. Let’s speak out to rest of the world to come and join hands to grow with us, this country has great potential, big brains who have done great innovations – we must be proud to have intellectuals like them, thank you so much for still having faith on this country! Team up Sri Lanka! and work with international communities to come to Sri Lanka. We will be successful for sure if we work together.
“Design” like a language, it’s versatile, it’s beautiful, it runs across many disciplines, it’s open to anyone, because of that many of us tries to learn about that language. Speaking of languages, everybody can’t learn or speak every language! Some people will try the basic and give it up, some of them are trying so hard to learn about it and when they fail, they will give up and they are never going to look back! For very few the language of design is their mother tongue, those people are born with that language, they are gifted with that language! They know how to speak it, control it, manipulate it, grow it, doing it so well that those people can create masterpieces just with few lines and curved edges! Language of design has no high or low! Design always maintains a middle ground, balanced ride, laser-focused middle path, always looking the balance between the logic and art, which logically and artistically bring balance to whatever the mess they going through! Language of design can bring peace, design can heal, design can bring tears to eyes, design can be a reason to happiness, design can end all fights, design can end many bad things in this world! This is an invitation to learn about design, Learn that language as much as you can! As much as you want! Do great things and design to bring peace!
What if, we could be able to share our brain power with each other! no more exams, no more tests, everybody knows everything, and everyone can understand everyone! end of fights, end of miss judgments, end of problems, end of war! finally, the world at peace! we can find peace together, the world is safe! we can think of building a much more safer world, together! so good to be true but love to believe.
OOCSS (Object Oriented Cascading Style Sheets), it seems new also quite a mouthful name but, it is a half a decade old concept that makes visuals in front of the web page more robust and dynamic, in another way this concept helps to implement styling on web pages, much larger scale with more efficient manner.
As a term “object” is something that consist, a state and a related behavior to that particular state, if we relate it to more practical way, an object stores its state in “fields” (variables in some programming languages) and reveal its behavior through “methods” (functions in some programming languages).
There are two principals to follow in this OOCSS, firstly “Separating the structure and the skin”. What this thing mean is to define repeating visual features such as background and border effects/styles as separate “skins” that we can combined or modified with various objects to achieve a large amount of visual data without putting too much code. There is another side, the separation of the skin and the structure means the classes to name the objects and their components, rather than depending just on the semantics of HTML. Referencing these kind of classes in our stylesheets, let’s say rather than directly styling the “<p>” (paragraph element). Its also flexible, for instance, when a new type of an element is about to introduce (e.g. ), it could be integrated into the HTML without having to touch the CSS.
Second principle is the “separation of container and content” this means “rarely use location-dependent styles”. An object should look the same no matter where we put it, instead of styling a specific element with a class, create and apply a class that describes the element.
This will give us an assurance that, all unclassed elements will look the same, all the elements with that category class(mixins) will look the same, also we don’t need to create a override style for the case when we actually do want that element with the class look like the normal element.
Data science is a collection of Data inference, algorithm development and technology, focusing on to solve analytically complex problems. At the center, there is data, there are more valuable raw information streaming through the Internet and stored in enterprise data warehouses, what data science doing is, using all that data in more intelligent and creative ways to process and produce insights/information which is used to generate business value, in other way data science helps us to do quantitative data analysis, to make strategic business decisions, just about anything.
There is a side of data science, it’s all about uncovering findings from data, it’s called “discovery of data insight”. whats happening with this is, we look at data in the smallest level we can, and with all the data mining tools, we can understand complex behaviors, trends. It’s about revealing hidden information that can help users and companies(mostly companies) to make smarter business decisions. Best example is “Netflix”, Netflix is a media streaming company which produce and streams movies and television series, with data science, they are uncovering data of movie viewing patterns to understand what users interested in, and using that information to make decisions on “which Netflix original series” to produce.
It happens with “data exploration” done by data scientists. When given a challenging and complex question, those data scientists become more like “detectives”. They investigate leads and understand patterns or characteristics in the data, this requires a huge amount of analytical creativity. After that if needed, data scientists may apply quantitative techniques to get more deep in to the problem, such as “time series forecasting”, “segmentation analysis”, “synthetic control experiments”. The main priority is to scientifically bring together a forensic view of what the data is really saying. This data-driven information/insights or the outputs, are the base, to provide strategic guidance. like detectives, data scientists act as consultants providing guidance to business stakeholders on how to act on data findings.
Another side of the data science is the “development of data product”, as a term a “data product” is a technical asset that utilizes data as input, and processes that data to return algorithmically-generated results, like recommendation engines. “recommendation engine” is a data product which absorb user data and makes personalized recommendations based on them. Google’s “Gmail spam filter” is a data product, in behind, a clever algorithm processes incoming mail and determines if that message is a spam or not.
But the “data product” is different from the “data insight” in data insights, the outcome of it provide advice to a business stakeholder to make a business decision, on the other hand a data product is a functionality includes algorithms, and designed to integrate directly in to core applications like “spam filter on Gmail’s inbox”, “Tesla’s autonomous driving software”. On developing data products, data scientists playing a key role in building out algorithms, testing and making refinements, they also involved in technical deployment of data products, into production systems. In this part the data scientists are serve as technical developers, designing and building assets that can be used in more wider scope.