A Quote by Robert Love
Realize you won't master data structures until you are working on a real-world problem and discover that a hash is the solution to your performance woes.
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Just like Pharaoh couldn't get a solution to his problem until he talked to Moses, or Nebuchadnezzar or Belshazzar couldn't get a solution to his problem until he talked to Daniel, the white man in America today will never understand the race problem or come anywhere near getting a solution to the race problem until he talks to The Honorable Elijah Muhammad.
The many woes that afflict out nation are rooted in the morally bankrupt paradigms of socialism, interventionism, and empire that have held our nation in their grip for decades and that the only real solution to such woes is libertarianism.
EMA research evidences strong and growing interest in leveraging log data across multiple infrastructure planning and operations management use cases. But to fully realize the potential complementary value of unstructured log data, it must be aligned and integrated with structured management data, and manual analysis must be replaced with automated approaches. By combining the RapidEngines capabilities with its existing solution, SevOne will be the first to truly integrate log data into an enterprise-class, carrier-grade performance management system.
Data dominates. If you've chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming.
Until you can see, and admit, that YOU are the problem... You will be unable to realize that YOU must be the solution.
TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue.
You know how it always is, every new idea, it takes a generation or two until it becomes obvious that there's no real problem. It has not yet become obvious to me that there's no real problem. I cannot define the real problem, therefore I suspect there's no real problem, but I'm not sure there's no real problem.
Recognizing a problem doesn't always bring a solution, but until we recognize that problem, there can be no solution.
Every startup should address a real and demonstrated need in the world - if you build a solution to a problem lots of people have, it's so easy to sell your product to the world.
Every startup should address a real and demonstrated need in the world. If you build a solution to a problem lots of people have, it's so easy to sell your product to the world.
There is no solution to any world problem, to any national problem, to any city problem or to any local problem, unless and until people get their Realization.
I think that there is only one way to science - or to philosophy, for that matter: to meet a problem, to see its beauty and fall in love with it; to get married to it and to live with it happily, till death do ye part - unless you should meet another and even more fascinating problem or unless, indeed, you should obtain a solution. But even if you do obtain a solution, you may then discover, to your delight, the existence of a whole family of enchanting, though perhaps difficult, problem children, for whose welfare you may work, with a purpose, to the end of your days.
The solution to a problem - a story that you are unable to finish - is the problem. It isn't as if the problem is one thing and the solution something else. The problem, properly understood = the solution. Instead of trying to hide or efface what limits the story, capitalize on that very limitation. State it, rail against it.
Learn when and how to use different data structures and their algorithms in your own code. This is harder as a student, as the problem assignments you'll work through just won't impart this knowledge. That's fine.
No matter how clear things might become in the forest of story, there was never a clear-cut solution, as there was in math. The role of a story was, in the broadest terms, to transpose a problem into another form. Depending on the nature and the direction of the problem, a solution might be suggested in the narrative. Tengo would return to the real world with that solution in hand. It was like a piece of paper bearing the indecipherable text of a magic spell. It served no immediate practical purpose, but it contained a possibility.
People believe the best way to learn from the data is to have a hypothesis and then go check it, but the data is so complex that someone who is working with a data set will not know the most significant things to ask. That's a huge problem.
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