81–90 of 131 posts
Start with a tutorial/pre-made script for one of the Kaggle Knowledge competitions. Move on to a real Kaggle competition and team up with someone who is in the same position on the learning curve as you. Use something like Skype or a Github repo to learn new tricks from one another.
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Because otherwise it should be called machine hallucinations? The process of learning could be defined as a task of extraction of relevant information (knowledge) about reality (shared environment) not mere accumulation of a fancy nonsense or false beliefs.
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 reality like: The actual sinking of the Titanic? If your model concludes that nobility, traveling first class, close to the exits, without family, has a higher chance of surviving…
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Lol. Predicting the survival of passengers on the Titanic is meaningless and misleading - there is literally no connection to reality, despite the framing of the task which suggests a certain connection. There is absolutely nothing that could be predicted. It is just a simulation of oversimplified model which describes nothing, but an oversimplified view of a historical event. It is as meaningless as the ant simulato…
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/Artificial_ants
Most of the models mimic and simulate (very naively) that observable behavior, not its origin.
When people cite "the map is not the territory" they mean this. Simulation is not even an experiment. It is mere an animation of a model - a cartoon.
Courses You MUST Take: 1. Machine Learning by Andrew Ng ( https://www.coursera.org/learn/machine-learning ) /// Class notes: ( http://holehouse.org/mlclass/index.html ) 2. Yaser Abu-Mostafa’s Machine Learning course which focuses much more on theory than the Coursera class but it is still relevant for beginners.( https://work.caltech.edu/telecourse.html ) 3. Neural Networks and Deep Learning (Recommended by Google Br…
HackerRank (YC S11) has one coming up in 2 weeks (filter by Domains > AI) [1].
I plan to participate as well just to explore the space. Feel free to shoot me a message if you'd like to discuss more.
DON'T LEARN NEURAL NETWORKS FIRST. Instead, learn decision trees and more importantly enough statistics so you aren't dangerous. Do you know what the central limit theorem is and why it is important? Can you do 5-fold cross validation on a random forest model in your choice of tool? Fine, now you are ready to do deep learning stuff. The reason I say not to do neural networks first is because they aren't very effectiv…
Thanks. Can you recommend any statistics books to be safe?
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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 reality like: The actual sinking of the Titanic? If your model concludes that nobility, traveling first class, close to the exits, without family, has a higher chance of surviving…
Correlations does not imply causation. There were many more relevant but "invisible" variables, which, probably, related to some genetic factors, like ability to sustain exposure to the cold water, ability to calm oneself down to avoid panic and self-control in general, strong survival instinct to literally fight the others, etc. The variables you have described, except the age of a passenger, are visible but irrelev…
In real life it is also very rare to have free pickings of the variables you want. Some variables have to substituted with available ones.
The Titanic story is to make things interesting for beginners. One could leave out all the semantics of this challenge, anonymize the variables and the target, and still use this dataset to learn about going from a table with variables to a target. In fact, doing so teaches you to leave your human bias at the door. Domain experts get beaten on Kaggle, because they think they need other variables, or that some variables (and their interactions) can't possibly work.
Let the data and evaluation metric do the talking.
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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/Artificial_ants
There is a very important notion from The Sciences of the Artificial book by Herbert A. Simon, that the visible (to an external observer) behavior of an ant (its tracks, if you wish) is not due to its supposed intelligence, but mostly due to the obstacles in the environment. Most of the models mimic and simulate (very naively) that observable behavior, not its origin. When people cite "the map is not the territory" t…
Simulation can be a very beneficial experiment. See for instance: https://papers.nips.cc/paper/5351-searching-for-higgs-boson-...