5 Ways To Learn Code From Your Own Browser
One of the big trends of the past couple years, spurred the growing demand for programmers, is the rise of in-browser programming tutorials. Gone are the days when you’d have to buy a book and configure a development environment before you could get your hands dirty with a little code. Maybe you want to start learning on your work computer and don’t have access to install a programming environment. Or maybe you want to get started right away and don’t want to deal with ordering books or installing software. 1. Eloquent JavaScript is actually a computer science book but it’s available on the web for free. 2. We’ve covered Codecademy and its mission to bring code literacy to the masses several times before. 3. Last week the Khan Academy revamped its computer science section to include a set of in-browser JavaScript tutorials. 4. Code School‘ offers a mix of free and paid in-browser courses, many of which are aimed at more accomplished programmers. 5. Bonus 1: Programr Bonus 2: Try Ruby
Simple math of everything
But for people who can read calculus, and sometimes just plain algebra, the drop-dead basic mathematics of a field may not take that long to learn. And it's likely to change your outlook on life more than the math-free popularizations or the highly technical math. Computer science Amdahl's law Relates the speedup of a sub-task to the resulting speedup of the whole. on Wikipedia, long with examples on MathWorld, short without examples Asymptotic notation Used to abstract away units and fixed overhead when analyzing resource usage. Deterministic finite state automata Traditional square one of theoretical computer science, with many practical applications. The pumping lemma for regular languages Illustrates many recurring themes. at Penn Engineering, explanation and examples handout (PDF) with concise statement and examples Cantor's diagonal argument An astonishingly elegant technique for proving certain kinds of theorems. on Wikipedia, definition and a step-through of the proof Halting Problem
Tutorials | Kaggle ML Data Science
This article is a stub. You can help us by expanding it. Tutorials by Kaggle Getting Started With Python For Data Science Our product wiz Chris introduces you to the use of the Python programming language for data science including environment setup and code examples. Getting in Shape for The Sport of Data Science (youtube.com) A tutorial by our chief scientist, Jeremy Howard, giving a brief overview of a (highly successful) data scientist's toolkit. Getting Started competitions Digit Recognizer The goal in this competition is to take an image of a handwritten single digit, and determine what that digit is. Titanic: Machine Learning from Disaster This competition, in which we ask you to predict who was likely to survive the wreck of the Titanic, provides an ideal starting place for people who may not have a lot of experience in data science and machine learning. Data Analysis in R twotorials: Two minute tutorials for R Learn how to do stuff in R in two minutes or less. 1. 2. 3. 4. 5. 6. Dr.
Machine Learning Andrew Ng Open-Classroom notes videos Stanford
Course Description In this course, you'll learn about some of the most widely used and successful machine learning techniques. You'll have the opportunity to implement these algorithms yourself, and gain practice with them. You will also learn some of practical hands-on tricks and techniques (rarely discussed in textbooks) that help get learning algorithms to work well. This is an "applied" machine learning class, and we emphasize the intuitions and know-how needed to get learning algorithms to work in practice, rather than the mathematical derivations. Familiarity with programming, basic linear algebra (matrices, vectors, matrix-vector multiplication), and basic probability (random variables, basic properties of probability) is assumed.
Hone your skills with bite-sized E-learning
Busy people rarely have time to hone their technical and business skills, yet it's critical to stay ahead of the curve. The solution? Online training. With most E-learning courses, you can proceed at your own pace in your own time (though a few instructor-led classes have fixed schedules). You can review material during a coffee break, or spend time on the laptop while your spouse is engrossed in a television show you can't stand. There are free training options, and some courses will even provide a credential or certificate to hang on your wall, while others provide the curriculum necessary to later pass a certification exam at an accredited testing agency. Whether you learn best by reading, listening or watching video - and you can find out at Learning Styles Online - there's is probably something that will suit your style. Adobe Adobe offers video training on Adobe TV. Microsoft The software giant offers an amazing collection of material, much of it free. Varied content Hewlett-Packard
Bite-Size Is the Right Size
By Sebastian Bailey, Ph.D., Co-Founder and President, Mind Gym We live in a culture of instant updates and short attention spans. We struggle to spend seconds away from our smart phones, never mind days out of the office in training. But that doesn’t mean personal development must sit on the back burner. From sermons to ancient Greek plays, piano lessons to TV documentaries, we have learned things in bite-size chunks for thousands of years. Bite-size Is Cheaper and More Effective Bite-size training achieves quicker outcomes without blowing the budget. It makes sense; it’s a good result to learn three things in a day. What Makes Bite-Size So Effective? Short, regular periods of high-intensity exercise get you fitter quicker than endurance training; eating little and often keeps you slimmer; and, likewise, bite-size training gets you to the learning outcome faster. What’s more, it’s easier to attend bite-size training. The Bite in Bite-Size It’s not just a case of shorter equals better. 1.
Recommended Courses @ MIRI - Machine Intelligence courses
by Louie Helm When I first learned about MIRI’s work, I assumed it was mostly a programming problem. As it turns out, it’s actually mostly a math problem. That’s because most of the theory behind self-reference, decision theory, and general AI techniques haven’t been formalized and solved yet. Thus, when people ask me what they should study in order to work on MIRI’s research, I say “Go study math and theoretical computer science.” But that’s not specific enough. I do, in fact, have specific recommendations for which subjects MIRI researchers should study. University courses. Have you already taken most of the subjects below? Not everyone cares about our research, and not everyone who cares should be a researcher. The Courses Outside Recommendations
