Ask HN: Machine learning/Data startups
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If you were talking about doing academic research in Machine Learning (ML), I would strongly recommend your way of approaching ML, i.e. exploring and learning different algorithms/models then trying to find a problem that can be used as a case for the model in hand. By doing this you're focusing more on the algorithm, which could lead to some advancement in the algorithm, but not necessarily leads to better products.
For a startup, I believe that you would get better results if you started by looking for a problem that you're passionate about or that you think it needs more development, and then you could apply the (right/best) ML algorithm/model to it.
For a startup, I believe that you would get better results if you started by looking for a problem that you're passionate about or that you think it needs more development, and then you could apply the (right/best) ML algorithm/model to it.
I'm a web developer working with Python and Django. Recently I've been playing with some ML toy problems and working through the Programming Collective Intelligence book in order to get an idea of the different possibilities available.
I realised there are a lot of different algorithms and a ton of different applications:
- Use social network data to identify users needs. - Predictive analysis(e.g. model future sales, cash-flows and expenses, packages volume...) - Find the best price of a product/service - Market analysis.
And many more...
As I am a begginer in this field, it's difficult to me to know how I should proceed in order to start a startup and make money with it. So I ask you if you have personal experience or know someone who's working in this kind of startups, what are you/they doing, how they began, how they decided in which kind of application to focus...
Right now I'm thinking of picking one or two topics, start playing with them and after a while see if I'm onto something or if I should look for other topics.
Thanks.