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The idea of artificial general intelligence as we know it today starts with a dot-com blowout on Broadway. Twenty years ago--before Shane Legg clicked with neuroscience postgrad Demis Hassabis over a shared fascination with intelligence; before the pair hooked up with Hassabis's childhood friend Mustafa Suleyman, a progressive activist, to spin that fascination into a company called DeepMind; before Google bought that company for more than half a billion dollars four years later--Legg worked at a startup in New York called Webmind, set up by AI researcher Ben Goertzel. Today the two men represent two very different branches of the future of artificial intelligence, but their roots reach back to common ground. Even for the heady days of the dot-com bubble, Webmind's goals were ambitious. Goertzel wanted to create a digital baby brain and release it onto the internet, where he believed it would grow up to become fully self-aware and far smarter than humans.

I became a data scientist because I like finding solutions for complex problems, the creative part of the job and the insights I gain from the data is what I enjoy the most. The boring stuff like cleaning data, preprocessing, and tuning hyperparameters brings me little joy, and that's why I try to automate these tasks as much as possible. If you also like automating the boring stuff you will love the library I am about to introduce in this article. As I mentioned in a previous article, the current state of the art in machine learning is dominated by deep learning in the case of perceptual problems and boosting methods for regression problems. Nobody is using the linear regression from Scikit-Learn to predict house prices in a Kaggle competition these days because the XGboost method is just more accurate.

The idea of artificial general intelligence as we know it today starts with a dot-com blowout on Broadway. Twenty years ago--before Shane Legg clicked with neuroscience postgrad Demis Hassabis over a shared fascination with intelligence; before the pair hooked up with Hassabis's childhood friend Mustafa Suleyman, a progressive activist, to spin that fascination into a company called DeepMind; before Google bought that company for more than half a billion dollars four years later--Legg worked at a startup in New York called Webmind, set up by AI researcher Ben Goertzel. Today the two men represent two very different branches of the future of artificial intelligence, but their roots reach back to common ground. Even for the heady days of the dot-com bubble, Webmind's goals were ambitious. Goertzel wanted to create a digital baby brain and release it onto the internet, where he believed it would grow up to become fully self-aware and far smarter than humans.

If you're an office worker, student, administrator, or just want to become more productive with your computer, programming will allow you write code that can automate tedious tasks. This course follows the popular (and free!) book, Automate the Boring Stuff with Python. Automate the Boring Stuff with Python was written for people who want to get up to speed writing small programs that do practical tasks as soon as possible. You don't need to know sorting algorithms or object-oriented programming, so this course skips all the computer science and concentrates on writing code that gets stuff done. This course is for complete beginners and covers the popular Python programming language.