Is this often done? Can you provide a reference explaining this further? Possibly specific to ML models.
79 karma · joined August 31, 2015
Even if you don't want to use the frameworks, you'll still have access to fast linear algebra routines.
If we say that we can't know for sure and give up, then no advancements would ever be made in any field. On the other hand, we should recognize that science does not claim to provide us with certainty. Many of us speaking "objectively" with scientific "facts" often become emotional and arrogant when speaking to anyone who doesn't agree with our conclusions.
They got what they wanted. I can't see what incentive they have as a business to grant access to the books that justifies paying employees for it.
My philosophy is that if I want to learn something, I get a few suggestions for books, briefly skim through their contents and pick one. After that I'll take notes in it and reread and basically squeeze every ounce of knowledge that I possibly can from it until it's engrained in my brain.
They seem to fill the void between in-depth study and knowing absolutely nothing.
That's not to say this isn't helpful. This is from my own personal experience.
Not saying I agree, but it could be the start of an interesting discussion.
"Why not just build M with neural nets from the beginning? Without the right data, neural nets couldn’t provide a service much more powerful than, well, Siri, and Wit.ai’s tech can get things started with relatively little data. “This is a good way to bootstrap. With a few thousand data-points, you can start to build a model,” Lebrun says. “Then, using this model, you get more data, and once you have about a million data points, you go to Yann and get some deep learning.”" [1]
He mentions that he used sklearn's Neural Network libraries in his blog post, but sklearn doesn't have any aside from RBM.
From Amazon: "This work stresses the illogical manner in which mathematics has developed, the question of applied mathematics as against 'pure' mathematics, and the challenges to the consistency of mathematics' logical structure that have occurred in the twentieth century."
From goodreads.com: "Most intelligent people today still believe that mathematics is a body of unshakable truths about the physical world and that mathematical reasoning is exact and infallible. Mathematics: The Loss of Certainty refutes that myth."
Edit: This was also interesting: https://www.youtube.com/watch?v=RlMMeqO7wOI , a video by Stephen Wolfram. I know he is often criticized for various reasons, but much of what he says makes intuitive sense.
Can someone address this? I've seen this put forth by many and Dawkins sounds very, very confused and completely avoids the question.