Machine learning and Data Science are cool, and really useful, but also they can be quite overwhelming when you are getting started, with complicated jargon and lots and lots of statistics and mathematical background. But, can we apply on it the long lasting Developer rule of “Hello world Now, Theory later”? In this talk I will share 5 tips from my journey becoming a Data Hacker, How the maker-mentality helped me become a better data-scientist, And how you can use your engineering strengths to become jack-of-all-trades Data Hacker.
12. Back-prop Regression Support vector
Convoluted network Association learning
Bayesian statistics Word2vec K-fold Chi-
quare Dimension reduction Sensetivity Over
Association learning True positive rate Data
cleaning Deep-learning Dimension Feature
ector Loss Regressor Random jungle poisso
distribution MSE MaxEnt Markov Chain
13.
14.
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16. The Hacker Way is an approach to
building that involves continuous
improvement and iteration. Hackers
believe that something can always be
better, and that nothing is ever
complete. They just have to go fix it —
often in the face of people who say it’s
impossible or are content with the
status quo.
Mark Zuckerberg
Machine learning Is a difficult topic to talk about.
It’s a topic full of buzz
I build shopping websites for a living
And when starting to learn ML, I went into a major block.
First theres the terminology.
Lot’s of terminology you need to grasp before you can evne start writing code
And then there the theoretical background.
A lot if it
With equation.
An di failed in math.
And that’s what’s today’s session is all about.
And that’s what’s today’s session is all about.
And here the definition is alittle different
And this is exactly what we are going to do today.
You might be joking here, but it’s actually a serious problem.
Because if I can spate geeky products from non-geek products I can create better recommendations for my geek clients.
And when you think a little deeper about it, it’s equivalent to questions like
“what is a fashionable product”
“what is an high quality product”
“would a deal seeker like this product?”
So.. What is a geeky product?
Let’s do a little quiz?
Batman statue is a geeky product.
Ok so we've learned batman toys are geeky
So we've learned toasters are not geeky.
Unless they are darth vader toasters.
Here it becomes tricky.
But we alno know only true geeks will be caught with fitbit bands.
Watches..
So now when
One approach is to get a specification from our product manager
And translate it to a giant piece of code full of if\else.
It doesn’t scale.
Impossible to test.
Impossible to debug, modify or change.
or
There is no shame in simple solutions
Simple ML will take you a long way
no reason It shouldn’t be be in your toolbox. As an engineer!
no reason It shouldn’t be be in your toolbox. As an engineer!
no reason It shouldn’t be be in your toolbox. As an engineer!
no reason It shouldn’t be be in your toolbox. As an engineer!
no reason It shouldn’t be be in your toolbox. As an engineer!