

Ask HN: What market demands can I solve with machine learning? - curiously

so while I&#x27;m learning machine learning I want to pursue some problems that are in demand by the market.<p>One example I can think of is a sentiment analysis on social media to measure some degree of product satisfaction. However, at one point can you confidently state that you&#x27;ve found the appropriate product satisfaction? What if there were errors along the way (NLP not working properly or false positives)? How would you consolidate such things to a client? Social media related machine learning seems dime a dozen anyhow.<p>I guess I am trying to employ the same philosophy to when I was learning how to program. Create something that is in demand by the market to best learn the trade. I want to do the same thing for machine learning, computer vision, but am not able to visualize what potential problems that are in demand by the market are worth pursuing.<p>So, what immediate problems do businesses or industries face that I can solve with machine learning?
======
tuscarok
How to determine what restaurants a person will like based on their past
ratings. This is not trivial; it is difficult to say what are the features
which determine why a person likes a restaurant, so I'm thinking this would be
a problem that could be tackled with deep learning i.e., automatic learning of
features rather than hand-crafting in advance.

This is similar to the problem of movie/book recommendations, which has not
been solved to my satisfaction. I have yet to see any good recommendation
systems out there which go beyond recommending movies based on simple things
like 'same actor was in this movie', 'people who watched that watched this'
etc.

~~~
gyre007
The problem with recommendations in general is that they are subjective to
people's feelings, often times at a particular point of time.

This is applicable to movies and restaurants. Sometimes I'm in a mood for an
action movie but that doesn't mean I want to be seeing those all the time
around. Similarly, there is simply time when I'm in a mood for mexican or
Indian and not Italian where I may have been going to for past month.

Unless we manage to capture the inner motivations/feelings (maybe based on our
online behavioural patterns?) our recommendations will just be artificially
built mashed potatoes crap.

------
nanoGeek
Machine learning is a hot topic today, like AI in general.

Facebook and Google use Machine learning algorithms to increase Ad revenue and
serve more relevant information to the user.

Machine learning is also used in health care to predict Emergency Room wait
times for example.

Many banks and big online retailers use Machine learning for fraud detection.

And of course Machine Learning is used in the stock market.

~~~
curiously
this is a very broad, top down look at the problems that are being solved but
I want to know a bottom up, an specific detail or the problems that is good to
tackle.

>ML in stock market

I know this is used here but what exactly? Mine tweets to predict stock prices
with a contrarian strategy? Computer vision on stock charts to apply technical
analysis trading system? Mine historical volatility of options on futures?

It would be great if there was some simple business or SaaS I can execute
using machine learning.

But say you have a website now with 'We use ML to solve X". Then the next
bigger challenge, convincing a business to fork over their data for the sake
of machine learning without previous experience. Or do you have to work for
free in the beginning to build credentials? 'Hey if you hand over your patient
data at your ER, we'll figure the waiting time out, never done this before
with another ER so we'll do it for free?'

I guess I'm interested in the applying entrepreneurial and business approach
to solve an actual real world problem that is in demand using ML.

~~~
ci5er
Anything that is manual, tedious and error-prone. Or requires quick reaction
time.

A "silly" example might be clinical diagnostic decision support. Instead of
charts with history, lab results and meds to visually wade through and
diagnose, there could be a simple UI. "Simple" means simply that instead of
potentially 1000 fields that might be read or selectively updated, there would
be 5 pre-selected by the computer. This could then go from medical
unstructured "narrative" to automated ICD-10 coding. There would be lots of
NLP, semantic analysis of large corpii, formal ontologies and RDF-encoded KB
tangles to work though.

> Computer vision on stock charts to apply technical analysis trading system?

Why would you use computer vision? Just get a DVD full of the intra-day tick
data for the instruments of interest going back 20-or-so years and find
correlations.

And, I'm sure you know this, but a reader wandering through here may not: many
of the kaggle competitions can be solved with ML techniques and many-or-most
of the solution types would be valuable to the market or to large (hopefully
funded) research problems. [https://www.kaggle.com/](https://www.kaggle.com/)

