I am currenly studying Civil Engineering, but i want to learn ML because it fascinates me. As a third year eng student, the maths doesnt bother me to much. I've just started working through Automate the Boring Stuff, to learn python. But should i finish this book, or should i just sign up to something like Dataquest and learn as i go? My concern is that it isn't really aimed at people who want to get into ML so how much of the knowledge is relevant.
Hey everyone, In short: I was wondering if the critic f in a Wasserstein GAN works similarly as the discriminator in standard GANs, i.e. is it still the case that I get high function values for x from the real distribution and small values for obvious fake images?
This is a new series, featuring forum questions (new and old) that are still popular today. These questions were selected manually based on popularity, removing outdated material. The entire series consists of about 160 questions -- most with answers, sometimes several answers. We intend to publish a new set every two weeks or so. The previous edition was posted here.
Best DSC Forum Questions - Part 4
Some early experiments and pics of an interactive convolutional boltzmann neuralnet are at http://github.com/benrayfield/timelessCellularAutomataPuzzleGame The patterns are much simpler than cats vs dogs, but its the turingCompleteness I think could make the game strategic, if gameplay is balanced, and various kinds of game design explored.
I'm very self driven and disciplined...I'm finishing my bachelors in chemistry and (along with basic analysis and linear algebra I got in school + some stat and probability that I have learned partly on my own) I learned Python and some R along with ML theory(elements of stat learning, deep learning book). I also tried doing some projects and read some research.
Python has a ton of plotting libraries—but which ones should you use? And how should you go about choosing them? This webinar shows you key starting points and demonstrates how to solve a range of common problems.
There are often close relationships between top level business metrics. For instance, it’s well known that retention has a super strong impact on the valuation of a subscription business. Or that the % of occupied seats is super important for an airline. A fun little toy model that I can up with generates a curious relationship between conversion rates and revenue.