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I am not particularly inclined to Math.
I do not have a Ph.D.
I do not like to read research papers.
But I do make a pretty good living working on the Data Science/AI/Machine Learning field.
You can also do it.
Here is how I got here.
I do not have a Ph.D.
I do not like to read research papers.
But I do make a pretty good living working on the Data Science/AI/Machine Learning field.
You can also do it.
Here is how I got here.
I started developing software very early and built my career as a Software Developer.
I feel that a strong foundation as a developer is a huge advantage in the field.
If you are exploring this path, do not skim on your Computer Science fundamentals!
I feel that a strong foundation as a developer is a huge advantage in the field.
If you are exploring this path, do not skim on your Computer Science fundamentals!
In 2015 I started taking classes in the field. Here are the relevant courses that I took:
- Machine Learning
- Reinforcement Learning
- Reinforcement Learning for Trading
- Computer Vision
Each one of these was one semester long. They gave me a good foundation of theory.
- Machine Learning
- Reinforcement Learning
- Reinforcement Learning for Trading
- Computer Vision
Each one of these was one semester long. They gave me a good foundation of theory.
On my own, I took the following classes:
- Machine Learning ( @AndrewYNg - Coursera)
- Deep Learning ( @AndrewYNg - Coursera)
- TensorFlow In Practice (Coursera)
- Reinforcement Learning by David Silverman (YouTube)
- Stanford Computer Vision (Fei-Fei Li - YouTube)
- Machine Learning ( @AndrewYNg - Coursera)
- Deep Learning ( @AndrewYNg - Coursera)
- TensorFlow In Practice (Coursera)
- Reinforcement Learning by David Silverman (YouTube)
- Stanford Computer Vision (Fei-Fei Li - YouTube)
I read books, watched many videos, and read many articles. I enjoyed very much Deep Learning with Python by @fchollet.
All of this has happened over the last 5 years and it's mostly the foundation of my knowledge.
(Yes, I had to read papers at school. But that's it.)
All of this has happened over the last 5 years and it's mostly the foundation of my knowledge.
(Yes, I had to read papers at school. But that's it.)
Approximately in 2018, I started transitioning from pure Software Engineering to a more Machine Learning-focused role.
The experience you get from "doing" is irreplaceable. You can't match it with all the courses in the world.
So early on, start creating things.
The experience you get from "doing" is irreplaceable. You can't match it with all the courses in the world.
So early on, start creating things.
After spending a long time focusing my work on more "Data Science" tasks, I found that my sweet spot is right at the intersection of Machine Learning and Software Engineering.
Right away I started learning everything I needed to be effective in this area.
Right away I started learning everything I needed to be effective in this area.
Day to day, my job varies, but it always centers around "productizing models".
Two words, a lot of work.
More specifically, I help answer this question: "How can we get this model that shows some promise and make it available for people to use in real-life scenarios?"
Two words, a lot of work.
More specifically, I help answer this question: "How can we get this model that shows some promise and make it available for people to use in real-life scenarios?"
The demand for this line of work is virtually limitless at this point and the supply is severely limited.
It's a great time to be alive!
Every year we make leaps on what we can do with the hardware, but we still need a lot of people to harness all of that power!
It's a great time to be alive!
Every year we make leaps on what we can do with the hardware, but we still need a lot of people to harness all of that power!
If you want to get into this field, here are some tips:
Software Development skills are a must.
A strong foundation on CS fundamentals helps.
Learn Python 
.
Containerization is a must (Hello @Docker!)
You will be building APIs. Flask / FastAPI will help.
Software Development skills are a must.A strong foundation on CS fundamentals helps.Learn Python .Containerization is a must (Hello @Docker!)You will be building APIs. Flask / FastAPI will help.
