why would you need to do a MATLAB implementation after writing it in C?
Because knowing how to implement something in C does not mean you know how to implement it in MATLAB, and the best way to learn to do both is to implement the same thing using both languages.
How many engineers do you think have used Kaggle to gain their employment?
I know two people personally who were asked, and bragged about, their Kaggle experience during ML engineer job interviews. Moreover, several of ML positions I was interested in had Kaggle experience mentioned as a desired qualification in the job description.
an engineer should be comfortable with working on the low level, understanding performance tuning and they should have a solid understanding of architecture on the low level
If you reread my comments, you will see that this was kind of my point (and a lot of people here disagreed with me on this). However, learning the details of the Linux kernel is not the best way to learn about computing, and is definitely not the best way to learn the skills needed to do machine learning.
do you even know what an engineer does?
Before enrolling in a PhD program, I worked as an engineer and an engineering manager for 12 years. Since I went back to school, I did two ML related internships, and I occasionally work on freelance ML projects for local companies.
What are your credentials, relevant to this discussion?
Because knowing how to implement something in C does not mean you know how to implement it in MATLAB, and the best way to learn to do both is to implement the same thing using both languages.
How many engineers do you think have used Kaggle to gain their employment?
I know two people personally who were asked, and bragged about, their Kaggle experience during ML engineer job interviews. Moreover, several of ML positions I was interested in had Kaggle experience mentioned as a desired qualification in the job description.
an engineer should be comfortable with working on the low level, understanding performance tuning and they should have a solid understanding of architecture on the low level
If you reread my comments, you will see that this was kind of my point (and a lot of people here disagreed with me on this). However, learning the details of the Linux kernel is not the best way to learn about computing, and is definitely not the best way to learn the skills needed to do machine learning.
do you even know what an engineer does?
Before enrolling in a PhD program, I worked as an engineer and an engineering manager for 12 years. Since I went back to school, I did two ML related internships, and I occasionally work on freelance ML projects for local companies. What are your credentials, relevant to this discussion?