Not to self advertise, but to use my own case to show that you can do some significant things if you're stubborn enough:
I'm self taught and under 3 years I'm collaborating with people at Stanford Research on an open source Question Answering System (https://github.com/SolrSherlock/) . I've also implemented my own stack for all of NLP that I'm working on contributing (summarization, sentiment analysis, named entity recognition,...)
You don't have to have a PHD to do it. Here's a bit of my background:
Coursera NLP class (first one from Stanford, not the later one)
AI class in college (Dropped out in year 3 though..so no masters or anything crazy)
Machine Learning class from coursera
Implementing and understanding LOTS of papers in the field
So as you can see not much. Most of my understanding is self taught. There's enough free materials out there for you to gain a practical understanding of it. Just take the time to build up your fundamentals and work from there. I have a practical understanding of the mechanics involved and can implement the different optimization algorithms and the like as well as understand the implications of the data.
Definitely as a specialty. However, branching in to other tasks is definitely appealing. My main thing would be computer vision to break in to next.
The main thing I'm going for here is "self-funded scientist" . I want to do something commercially viable while solving problems I enjoy doing.
Being that running a company (even a life style one) takes a decent chunk of time. I can't devote the time to other branches of machine learning that I'd like.
That being said, I'll be investing time in the upcoming computer vision class (albeit to maybe finish the material, the certifications can be a good chunk of time)
I think as time moves on I'll move in to other areas, but if I do some kind of project or even just building out something major, I want to at least have a chance of monetizing the technology.
In this case, with NLP there's a breadth of technologies, apps, and ideas that you can do using that as a baseline platform.
Computer Vision is the same way. Admittedly, I'm not as familiar with the different ways of commercializing it as I am NLP.
It's also something I've been wanting to do for a long time.
When Watson debuted, I had wanted to be in the space for a
long time.
We'll see what happens as time goes on.
Right now being able to run something as well as collaborate with some of the smartest people I've ever seen on an open source project has me in a pretty good spot.
Comments
Not to self advertise, but to use my own case to show that you can do some significant things if you're stubborn enough:
I'm self taught and under 3 years I'm collaborating with people at Stanford Research on an open source Question Answering System (https://github.com/SolrSherlock/) . I've also implemented my own stack for all of NLP that I'm working on contributing (summarization, sentiment analysis, named entity recognition,...)
You don't have to have a PHD to do it. Here's a bit of my background:
Coursera NLP class (first one from Stanford, not the later one)
AI class in college (Dropped out in year 3 though..so no masters or anything crazy)
Machine Learning class from coursera
Implementing and understanding LOTS of papers in the field
So as you can see not much. Most of my understanding is self taught. There's enough free materials out there for you to gain a practical understanding of it. Just take the time to build up your fundamentals and work from there. I have a practical understanding of the mechanics involved and can implement the different optimization algorithms and the like as well as understand the implications of the data.
Congrats, you've definitely worked hard to get where you are!
How do you feel about non-NLP tasks? Are you focusing on NLP as a specialty, or using it to branch out into other tasks?
Definitely as a specialty. However, branching in to other tasks is definitely appealing. My main thing would be computer vision to break in to next.
The main thing I'm going for here is "self-funded scientist" . I want to do something commercially viable while solving problems I enjoy doing.
Being that running a company (even a life style one) takes a decent chunk of time. I can't devote the time to other branches of machine learning that I'd like.
That being said, I'll be investing time in the upcoming computer vision class (albeit to maybe finish the material, the certifications can be a good chunk of time)
I think as time moves on I'll move in to other areas, but if I do some kind of project or even just building out something major, I want to at least have a chance of monetizing the technology.
In this case, with NLP there's a breadth of technologies, apps, and ideas that you can do using that as a baseline platform.
Computer Vision is the same way. Admittedly, I'm not as familiar with the different ways of commercializing it as I am NLP.
It's also something I've been wanting to do for a long time.
When Watson debuted, I had wanted to be in the space for a long time.
We'll see what happens as time goes on.
Right now being able to run something as well as collaborate with some of the smartest people I've ever seen on an open source project has me in a pretty good spot.