He guys, I just want to get into ML field. After some research I made a roadmap below.
I am a huge fan of udemy, and video courses as a whole, it is just the way I absorb the information.
It is going to be a quite long journey so I am looking for your advice whether I need certain course or not.
Currently I am working as a reactjs dev with C#/mssql backend.
If you find the courses on Udemy suite your learning style, then go for it. As for others recommending which to take/leave out, it depends on many factors.
Specifically, you have linked many courses that focus on the mathematics involved in machine learning. Whilst knowing these topics is relevant, I would encourage more practical programming examples to learn the maths. That being said, it does depend on your academic background. I have covered Maths to the point that I would be bored with anything more than a passing mention of the methods used in ML.
Still, I will encourage you to implement the methods, more so than spend hours on the theory.
Hi man, thanks for your advice.
I studies statistics and applied math in univercity since my major is business administration.
But since I do not remember anything except terminology I guess all these theoretical stuff can be helpful as a refresher.
And since I enjoy sitting and studying some stuff, I am not getting bored you know )))
My roadmap is planned for 2020 and in 2021 I think I will have enough knowledge and foundation to apply for ML eng job.
Do you work as a ML eng? Just was curious about the insights of this field.
No, I do not work as a machine learning engineer. My job does involve machine learning, but it is much broader than that. It is purely out of my own personal interest I learn it.
Whilst completing online tutorials, and potentially getting a degree in CS, is useful, I would imagine you will need some other engineering experience before being able to apply for an ML Engineer role.
In terms of the computer science behind ML, anyone hoping to get a job developing in this field will need to have extensive knowledge around algorithms for data manipulation. So, perhaps studying something similar to kNN, K-Means, Regression, and Reduction would benefit you. I assume you will have come across Naive Bayesian models - statistics comes in heavily here.
