BickNowstrom

19 ms·

121.
by BickNowstrom 10y ago
I actually think Machine Learning is relatively easy. There are a lot of resources, the community is very open, state-of-the-art tools are available, and all it needs to get incrementally better is trying out more stuff on different data se
122.
by BickNowstrom 10y ago
Learn Python stack: scipy, numpy, pandas, scikit-learn, jupyter, matplotlib/seaborn. Learn machine learning tools: XGBoost, Scikit-learn, Keras, Vowpal Wabbit. Do data science competitions: Kaggle, DrivenData, TopCoder, Numerai. Take t
123.
by BickNowstrom 10y ago
> ... so badly fooled while obscuring such a small amount of the face ... may go completely off the rails when presented with data not close enough to their training sets. Older research has looked at this, in the context of neural netw
124.
by BickNowstrom 10y ago
Since the added noise is not just noise, but especially engineered perturbations to maximally activate the output neurons for a certain class -- if you want to draw a comparison to humans, one could look at the hyperstimulus/supernorma
125.
by BickNowstrom 10y ago
Ensembles are also vulnerable to adversarial images. From one of the canonical papers on adversarial images: > In addition, the specific nature of these perturbations is not a random artifact of learning: the same perturbation can cause
126.
by BickNowstrom 10y ago
You are right, but only in a very strict, not-fun, manner :). Even if we had more data on different boats sinking, the model would not be very useful: We don't go with the Titanic anymore and plotted all icebergs. Still, if a cruise sh
127.
by BickNowstrom 10y ago
The people who win Kaggle competitions are consistently machine learning experts, not domain experts. Notably: https://www.kaggle.com/c/MerckActivity > Since our goal was to demonstrate the power of our models, we d
128.
by BickNowstrom 10y ago
Because we are not doing hypothesis testing, we are doing classification on a toy dataset. Sure, one could treat this as a forecasting challenge, but then one would need another Titanic sinking in roughly the same context, with the same fea
129.
by BickNowstrom 10y ago
It is swarm intelligence: How does the system keep finding successful paths in a changing environment? Can we take inspiration from this behavior to create better optimization algorithms? Simulation can be a very beneficial experiment. See
130.
by BickNowstrom 10y ago
This challenge is not about causal inference. I do agree it is more of a toy dataset, to get started with the basics, and that there are a lot of other variables that go into survivability. But to say these variables, except for age, are ir
131.
by BickNowstrom 10y ago
Everybody learns differently, but I would suggest starting with the how, not the what. Compare: How do I sort a list? With: What is exactly happening when I sort a list? Application before theory. Start with a tutorial/pre-made script
132.
by BickNowstrom 10y ago
So knowledge like: Did the passenger have kids on board? Was the passenger nobility? Was the passenger travelling first class? Where was the passenger located on the ship after boarding? And how do these factors influence survivability? And
133.
by BickNowstrom 10y ago
You seem to be saying a whole lot without backing up your argument. If anything, your view is meaningless. https://en.wikipedia.org/wiki/Ant_colony_optimization_algori... https://en.wikipedia.org/wiki&#
134.
by BickNowstrom 10y ago
This entire blog post does not cast the author in a favourable light. First off: It is rude to post the questions and expected answers, perhaps moreso when you just failed to pass the test yourself. That reeks of sabotage out of spite. Then